issues in mobile distributed real time databases

Vishnu Swaroop et al. / International Journal of Engineering Science and Technology (IJEST)

ISSUES IN MOBILE DISTRIBUTED REAL TIME DATABASES: PERFORMANCE AND REVIEW VISHNU SWAROOP Computer science & Engineering Department, M M M Engineering College, Gorakhpur, UP 273010, INDIA

Gyanendra Kumar Gupta Computer science & Engineering Department, Kanpur Institute of Technology, Roma, Kanpur, UP 208 001, INDIA

UDAI SHANKER Computer science & Engineering Department, M M M Engineering College, Gorakhpur, UP 273010, INDIA Abstract : Increase in handy and small electronic devices in computing fields; it makes the computing more popular and useful in business. Tremendous advances in wireless networks and portable computing devices have led to development of mobile computing. Support of real time database system depending upon the timing constraints, due to availability of data distributed database, and ubiquitous computing pull the mobile database concept, which emerges them in a new form of technology as mobile distributed realtime database systems. Processing of transaction with mobility as well as time constraints has opened up a new area of research with a number of design issues such as network connectivity, storage capacity, scheduling, data consistency, data replication & distribution, concurrency control & commit processing, reliability, security, economical aspect etc. In fact, this paper first discusses the performance issues that are important to MDRTDB, and then surveys the research that has been done so far. The predictability of a MDRTDB is affected by a manner by a number of factors such as concurrency control, priority scheduling, commitment and mobile wireless communications. Keywords: Transaction Scheduling, Consistency, Security, Mobile Distributed Real Time Database. 1. Introduction Modern technologies have provided portable computers with wire-less interfaces that allow networked communication even while a user is mobile. Wireless networking greatly enhances the utility of a portable computing device. The combination of networking and mobility will engender new technical challenges that mobile computing must surmount to achieve under investigation and also consider their limitations. In the last few years, the use of portable computers and wireless networks has been widespread. The combination of both opens the door to a new technology: mobile computing. Although the wireless communication networks were designed for the transport of voice signals, their use for data transport is growing. Mobile computing allows users to access from anywhere and at anytime the data stored in repositories of their organizations (i.e. the DBs of the company in which they work) and also for available data in a global information system through Internet. Computers are typically configured for use in a single location. The shift toward mobility and wireless communication is testing the abilities of designers to adapt traditional system structures. Many professionals use mobile computers for their work: sales personnel, emergency services etc. in order to obtain and send information in the place where and at the moment when they actually need it. Moreover, there exist applications in this new framework where the location is an important aspect, such as those that provide information about the nearest hotels, restaurants, etc. That is, mobile computing mainly depends upon the stored database and their transaction, adds a crucial challenges for the researchers. [Alfredo (2000)]

The ability to change locations while connected to the network increases the volatility of some information. Certain data considered static for stationary computing becomes dynamic for mobile computing. For example, a

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stationary computer can be configured statically to prefer the nearest server, but a mobile computer needs a mechanism for determining which server to use. As volatility increases, cost-benefit trade-off points shift, calling for appropriate modifications in the design. For example, a highly volatile data object has fewer uses per modification. For such objects it makes little sense to cache the data. As another example, consider static information, which is often managed by hand; to handle higher rates of change, automated methods are required. However, even where such methods exist, they may be ill-suited for the dynamism of mobile computing. Mobility introduces several problems: A mobile computer's network address changes dynamically, its current location affects configuration parameters as well as answers to user queries, and the communication path grows as it wanders away from a nearby server. Address migration. As people move, their mobile computers will use different network access points, or "addresses." Today's networking is not designed for dynamically changing addresses. Active network connections usually cannot be moved to a new address. Once an address for a host name is known to a system, it is typically cached with a long expiration time and with no way to invalidate outof-date entries. In the Internet Protocol, for example, a host IP name is inextricably bound with its network address; moving to a new location means acquiring a new IP name. Human intervention is commonly required to coordinate the use of addresses. To communicate with a mobile computer, messages must be sent to its most recent address. Today’s Information Era database is essential component of any Information system and in any environment either it is traditional, distributed, network, real-time or mobile. Data and the way it is organized is very important in any system. A database is a structured way to organize information. This could be a list of contacts, price, information or distance traveled. As the database grows vastly the management of database is a big challenge for database manager. To manage the database in more meaningful and organized way there are several methods for accessing the database in any system. Databases are great at dealing with large amounts of data that need to be searched, sorted, or regularly updated. Databases are used pretty much everywhere. Data processing played a big part in the development of computers, and even today it is one of their main roles. Nearly every walk of life or business requires a database somewhere along the way. Databases are commonly used on personal computers to store data used locally, and on company networks databases store and share company-wide information. Popularity of Internet has seen a big rise in databases used to share information; most online system of a reasonable size use databases. A properly set-up database minimizes data redundancy. Databases are fragmented both horizontally and vertically and are store at different places for security and failure reasons. Thus it is very important that when the databases are fragmented at different places consistency is major things before security and backup of databases. Databases also allow us to set up rules that ensure that data remains consistent when we make transactions i.e. add, update, or delete data. A database that consists of two or more data files located at different sites on a computer network is known as distributed database systems. Hence, distributed database is a collection of multiple, logically interrelated databases distributed over a computer network. A distributed database management system is a software system that permits the management of the distributed database and makes the distribution transparent to the users. Because the database is distributed, different users can access it without interfering with one another. However, the DBMS must periodically synchronize the scattered databases to make sure that they all have consistent data. The distributed database systems consist of a collection of sites, connected together via wired networks, in which, each site is a database system site in its administrative rights but the sites have agreed to work together, so that a user at any site can access data from anywhere in the network, exactly as if, the data are all stored at the user’s own site [Lee (1998), Barbará(1999)]. Centralize databases are persistent but are incapable of processing with dynamic data that constantly changes. Therefore, another system is needed. Real-time databases may be modified to improve accuracy and efficiency and to avoid conflict, by providing deadlines and wait periods to insure temporal consistency. Realtime database systems provide a way of processing a physical system and representing it in data streams to a database. A data stream, like memory, fades over time. In order to guarantee that the latest and most accurate information is recorded there are a number of ways of checking transactions to make sure they are executed in the proper order. Present database systems are faster than they were in the past. In the future, we can look forward to even faster database systems. Today’s faster systems are now available to reduce misses and tardy times will still be beneficial. The ability to process results in a timely and predictable manner will always be more important than fast processing. Fast processing that is misapplied is not helpful for real-time database systems. Transactions that run faster still sometimes block in such a way that they have to be aborted and restarted. In fact, faster processing hurts some real-time applications because increased speed brings more complexity and more of a chance for problems caused by a variance of speed. Faster processing makes it harder to determine which deadlines have been met successfully. With future database systems running even faster than ever, there is a need to do more studies so we can continue to have efficient systems [Bestavros (1997)].

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More of research studying real-time database systems will increase because of commercial applications such as online web based system. Studies of temporal consistency result in new protocols and timing constraints with the goal of handling real-time transactions more effectively [Ramamritham (1993]. A real-time database is a processing system designed to handle workloads whose state is constantly changing. This differs from traditional databases containing persistent data, mostly unaffected by time. Realtime applications are increasingly being implemented on different platforms like centralize, distributed and mobile. In a real-time database system, timing constraints are associated with transactions, and data are valid for specific time intervals. The transaction timing constraints can be completion deadlines, start times, periodic invocations, and so on. It is not necessary that every transaction have a timing constraint, only that some do. In addition to transaction timing requirements, data has time semantics as well. Data such as sensor data, stock market prices, and locations of moving objects all have semantics indicating that the recorded values are valid only for a certain time interval. A real-time database makes this validity interval explicit as part of its database schema. Real-time databases are traditional databases that use an extension to give the additional power to give up reliable responses. They use timing constraints that represent a certain range of values for which the data are valid. This range is called temporal validity. A conventional database cannot work under these circumstances because the inconsistencies between the real world objects and the data that represents them are too severe for simple modifications. An effective system needs to be able to handle time-sensitive queries, return only temporally valid data, and support priority scheduling. To enter the data in the records, often a sensor or an input device monitors the state of the physical system and updates the database with new information to reflect the physical system more accurately. When designing a real-time database system, one should consider how to represent valid time, how facts are associated with real-time system. Also, consider how to represent attribute values in the database so that process transactions and data consistency have no violations. When designing a system, it is important to consider what the system should do when deadlines are not met. For example, an airtraffic control system constantly monitors hundreds of aircraft and makes decisions about incoming flight paths and determines the order in which aircraft should land based on data such as fuel, altitude, and speed. If any of this information is late, the result could be devastating. To address issues of obsolete data, the timestamp can support transactions by providing clear time references. As real time system (RTS) continue to evolve, their applications become more and more complex, and often require timely access and predictable processing of massive amounts of real time data. The database systems, which are especially designed for the efficient processing of these types of real time data, are referred to as distributed real-time database systems (DRTDBS). Thus, DRTDBS are collection of multiple, logically interrelated databases distributed over a computer network where transactions have explicit timing constraints, usually in the form of deadlines. In such a system, data items shared among transactions are spread over remote locations. In real Time Database System, the transactions have to be completed before their fixed schedule time and all the completed transaction before the fixed schedule time must be effected the validated changes [Kayan (1999), Imielinski (1996)]. Real Time systems are those for which correctness depends not only on the logical properties of the produced results, but also on the temporal properties of these results. In general, the real time systems are related with significant applications, in which live transactions being at risk and so in such systems the action perform uncertainty after the deadline. In real time system the computation which uses temporally unacceptable data may be useless and sometimes dangerous even if such an action or computation is functionally correct. In real-time databases, deadlines are formed and different kinds of systems respond differently to data that does not meet its deadline. In a real-time system, each transaction uses a timestamp to schedule the transactions (Abbot). A priority mapper unit assigns a level of importance to each transaction upon its arrival in the database system that is dependent on how the system views times and other priorities. A real-time database system (RTDBS) is a transaction processing system where transactions have explicit timing constraints. Typically, a timing constraint is expressed in the form of a deadline, a certain time in the future by which a transaction needs to be completed. A deadline is said to be hard if it cannot be missed or else the result is useless. If a deadline can be missed, it is a soft deadline. With soft deadlines, the usefulness of a result may decrease after the deadline is missed. In RTDBS, the correctness of transaction processing depends not only on maintaining consistency constraints and producing correct results, but also on the time at which a transaction is completed. Transactions must be scheduled and processed in such a way that they can be completed before their corresponding deadlines expire. Real-time database systems are being used for a variety of applications such as process control, mission critical applications in command and control systems and radar systems, computer integrated manufacturing systems, and air traffic control systems, among others. Conventional data models and databases are not adequate for time-critical applications, since they are not designed to provide features required to support real-time transactions. They are designed to provide good

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average performance, while possibly yielding unacceptable worst-case response times. Very few of them allow users to specify or ensure timing constraints. During the last few years, several research and development efforts on RTDBSs have been reported [Ramamritham (1990 ), Son(1990), Rosenthal(1998), Yu(1994) ]. A distributed database system allows applications to access data from local and remote databases. Typically, distributed database applications use distributed transactions to access both local and remote data and modify the global database in real-time.

Distributed computing allows different users or computers to share information. Distributed computing can allow an application on one machine to leverage processing power, memory, or storage on another machine. It is possible that distributed computing could enhance performance of a stand-alone application, but this is often not the reason to distribute an application. Some applications, such as word processing, might not benefit from distribution at all. In many cases, a particular problem might demand distribution. If a company wishes to collect information across locations, distribution is a natural fit. In other cases, distribution can allow performance or availability to be enhanced. If an application must run on a PC and the application needs to perform lengthy calculations, distributing these calculations to faster machines might allow performance to be enhanced. Database performance is an important aspect of database usability. Distributed real time database systems (DRTDBS) must be designed on all levels of database architecture to support timely execution of requests. The primary performance objective in DRTDBS is to minimize the number of missed deadlines. Due to the demanding nature of this objective, traditional approaches are inadequate. However, the research in DRTDBS has been mostly devoted to extending traditional transaction processing techniques to solve the issues important for the design of DRTDBS. In this environment, new policies and protocols must be designed to efficiently handle the transactions execution. [Udai Shanker (2006)]. Distributed database systems (DDBS) pose different problems when accessing distributed and replicated databases. Particularly, access control and transaction management in DDBS require different mechanism to monitor data retrieval and update to databases. Current trends in multi-tier client/server networks make DDBS an appropriated solution to provide access to and control over localized databases. Oracle, as a leading Database Management System (DBMS) vendor employs the two-phase commit technique to maintain consistent state for the database. The objective of this paper is to explain transaction management in DDBS and how Oracle implements this technique. An example is given to demonstrate the step involved in executing the two-phase commit. By using this feature of Oracle, organizations will benefit from the use of DDBS to successfully manage the enterprise data resource. Performance and cost to handle the mobile distributed database management in a business not only affect the business it also raises many problems. Performance of mobile distributed database system is heavily dependent on allocation of data among different sites, because major cost is executing queries in a mobile distributed database system is the data transfer cost incurred in moving data accessed by a query from different sites to site where the query is initiated. The static location provides only limited response to changing workload. Many algorithms is proposed for the distributed database system for non-replicated distributed database. But still more to do for replicated distributed database. The mobility is also a constraint for mobile distributed database, limited bandwidth , frequent dis-connection and failure increase the complication in available methods [Arjan Singh (2009)]. Caching plays a key role in mobile computing because of its alleviate the performance and availability limitations of weakly-connected and disconnected operations. But evaluating alternative caching strategies for mobile computing is problematic. Today, the only metric of cache quality is the ratio. The underlying assumption of this metric is that all cache misses are equivalent (that is, all cache misses exact roughly the same penalty from the user). This assumption is valid when the cache miss is small and, to a first approximation, independent of the file length. But the assumption is unlikely to be valid during disconnected or weaklyconnected operation. The miss ratio also fails to take into account the timing of misses. To be useful, new caching metrics must satisfy two important criteria. First they should be consistent with qualitative perceptions of performance and availability experienced by users in mobile computing. Second, they should be cheap and easy to monitor. The challenge is to be developing that what is an appropriate set of caching metrics, under what circumtance4s does it use, how it efficient to monitor does and what are the implications of these alternative metrics for caching in mobile computing [M Satyanarayan (1996)]. Mobile Computing requires wireless network access, although sometimes – when in meeting rooms or at a users desk – they may remain stationary long enough to be physically attached to the network for a better or cheaper connection. Wireless networks communicate by modulating radio waves or pulsing infrared light. Wireless communication is linked to the wired network infrastructure by stationary transceivers. Wireless communication faces more obstacles that wired communication because the surrounding environment interacts

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with the signal, blocking signal paths and introducing noise and echoes. As a result, wireless communication is characterized lower bandwidths, high error rates, and more frequent spurious disconnections. These factors can in turn increase communication latency resulting from retransmissions, retransmission time-out delays, errorcontrol protocol processing and short disconnections. Mobility can also cause wireless connections to be lost or degraded. Users may travel beyond the coverage of network transceiver or enter areas of high interference. Unlike typically wired networks, the number of devices is a network cell varies dynamically, and large concentrations of mobile users say. Conventions and public events, may over loaded network capacity [M. Weiser (1993)]. Recent advances in hardware technologies such as portable computers and wireless communication networks have led to the emergence of mobile computing systems and mobile database systems Mobile database is a database that can be connected via a mobile computing device over a mobile network. The client and server have wireless connections. A cache is maintained to hold frequent data and transactions so that they are not lost due to connection failure [Patricia Serrano-Alvarado (2001)]. For example, in most devices, the email facility is commonly used even when in mobility of user. Another use is entertainment i.e. online multimedia games which are becoming very popular application and use the database continuously. Listening of online music with different service provider through their websites is more popular nowadays. The growth of digital technology provides the digital contents in the form of digital music and movie which are the very popular example of mobile application. Mobile Real-time systems often need to manipulate large amounts of shared data, which naturally leads to the use of DBMSs. However, traditional database management systems are of little use in real-time systems, since such systems impose new requirements that are not satisfied in traditional DBMSs. Advanced mobile application uses the highly and heavily dense multimedia database. These applications have verifying/authorizing ones credit card, inventory data, transfer of funds and many more which must have importance of reliability and dependability. The communication network is an important challenge, which is an essential issue for MDRTDBS. Both wired and wireless connection is used to provide the communication channel for Mobile Network. In the world of computers, networking is the practice of linking two or more computing devices together for the purpose of sharing data. Networks are built with a mix of computer hardware and computer software. Networks can be categorized in several different ways. One approach defines the type of network according to the geographic area it spans. Local area networks (LANs), for example, typically reach across a single home, whereas wide area networks (WANs), reach across cities, states, or even across the world. The Internet is the world's largest public WAN. A local area network (LAN) supplies networking capability to a group of computers in close proximity to each other such as in an office building, a school, or a home. A LAN is useful for sharing resources like files, printers, games or other applications. A LAN in turn often connects to other LANs, and to the Internet or other WAN. Specialized operating system software may be used to configure a local area network. For example, most flavors of Microsoft Windows provide a software package called Internet Connection Sharing (ICS) that supports controlled access to LAN resources. A WAN spans a large geographic area, such as a state, province or country. WANs often connect multiple smaller networks, such as local area networks (LANs) or metro area networks (MANs). The world's most popular WAN is the Internet. Some segments of the Internet, like VPNbased extranets, are also WANs in themselves. Finally, many WANs are corporate or research networks that utilize leased lines. Wireless networks utilize radio waves and/or microwaves to maintain communication channels between computers. Wireless networking is a more modern alternative to wired networking that relies on copper and/or fiber optic cabling between network devices [.Patricia (2004 )]. A wireless network offers advantages and disadvantages compared to a wired network. Advantages of wireless include mobility and elimination of unsightly cables. Disadvantages of wireless include the potential for radio interference due to weather, other wireless devices, or obstructions like walls. Wireless is rapidly gaining in popularity for both home and business networking. Wireless technology continues to improve, and the cost of wireless products continues to decrease. Considering the above system, MDRTDS require a lot of research efforts to be carried to meet out the challenges.

2. Challenges in MDRTDBS With the rapid growth of wireless networking technology and mobile computing devices, a highly increasing demand arises for processing mobile transactions in MDRTDBS. This allows mobile users to access and manipulate data anytime and anywhere. However, to guarantee timely access and correct results for concurrent mobile transactions, concurrency control (CC) techniques become critical. Due to the characteristics of databases, existing mobile distributed real time database CC techniques cannot work effectively. This paper

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discusses the issues that need to be addressed when designing a CC technique for MDRT databases, and reviews related techniques with respect to those issues. 2.1. Mobility: The ability to change nodes’ locations while retaining network connection is the key motivation of Mobile computing. However, a node’s network and physical location change dynamically, and at the same time, the states of transactions and accessed data items have to move along with the node. These changes affect the system configuration parameters of the node and those of other nodes like the routing information in the routing tables and affect those transactions executed on the node. Mobility can also lead to multi-hop communication, high communication latency, frequent disconnections and long-lived transactions. 2.2. Low bandwidth: Wireless network bandwidth is much lower than its wired counterpart. For example, the widely used 802.11b wireless card has a maximum data rate of 11 Mbit/s [Ed. Van Sickle (2007)] and the latest 802.11g wireless card supports data transmission up to 54 Mbit/s ; however, currently an affordable Gigabit Ethernet card realizes a maximum data rate of 1000 Mbit/s [R. Zimmermann (2005)]. Thus, within the cell of one node, inside neighbors have to share and compete for the same channel. If someone fails, it may keep sending requests until timeout. This low bandwidth can result in communication delays, a high risk of disconnections and longlived transactions as well. 2.3. Multi-hop communication: In traditional mobile networks, mobile nodes that communicate with each other must go through a fixed infrastructure. While in MANETs, nodes can communicate with each other either directly or via other nodes that function as routers. When communication goes more hops, more power and bandwidth are consumed, and more execution time is needed to complete transactions. 2.4. Limited battery power: Because of the mobility and portability, clients and servers have severe resource constraints in terms of capacity of battery and sizes of memory and hard drive. In addition, the battery technology is not developed as rapidly as the mobile devices and wireless technologies. For instance, a fully-charged Dell Latitude C600 laptop can run about 3.5 hours, which is estimated by well-known industry battery life benchmarks [G. Verdun (2005)]. When processing power is limited, it compromises the ability of each mobile node to support services and applications [I. Chlamtac (2003)]. Once a node runs out of power or has insufficient power to function, communication fails, disconnections happen, execution of transactions is prolonged, and some transactions may have to be aborted. 2.5. Limited storage: Due to mobility and portability, the sizes of memory and hard drive are smaller than the ones in the wired network. The consequences of this are less stored/cached/replicated data, fewer installed applications, and more communication. 2.6. Frequent disconnections: A node is disconnected when it roams freely and is out of the transmission range of all its neighbors, it fails to compete for the channels of popular neighbors, its battery runs out, or it runs into some failures. It is normal for a node to become disconnected in MANETs, and such disconnections do not always imply the failure of transactions initiated or executed by the disconnected node because the disconnected node may reconnect after some time. While disconnected, the disconnected node may still be able to process part of already started transactions. However, when disconnections happen frequently, more transactions may be delayed or blocked, and even aborted if they are real-time and missed their deadlines. 2.7. Long-lived transactions: Due to mobility, wireless communication delay, less processing power, frequent disconnections and unbounded disconnection time, transactions in MANETs databases tend to be long-lived. When the execution is

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prolonged, the probability of conflicts with other transactions becomes higher and, consequently, transactions are likely blocked if a pessimistic CC method applies or restarted if an optimistic CC method is in use. 2.8. Small user Interface: Size constraints on a portable computer require a small user interface. Desktop windowing environments may be sufficient for today’s notebook computers, but for smaller, more portable devices, current windowing technology is inadequate. On small displays it is impractical to have several windows open at a time regardless of screen resolution, and it can be difficult to locate windows or icons deeply stacked one another. Also windows title bars and borders either consume significant portions of screen space or, if reduced, become difficult to operate with pointing devices. Mobile Distributed Real Time database research is still in the early stage. To the best of our knowledge, so far only one CC algorithm has been proposed [A. Brayner, (2005)]; however, it does not take into account all the identified characteristics of MDRT databases. The existing CC techniques for traditional mobile network databases, in which only clients are mobile and battery-powered, cannot be directly applied because of these characteristics either. In this paper, we identify the design issues inherent to CC techniques for client-server MDRT databases, review how current existing mobile database CC techniques handle these issues and address MDRT characteristics at the same time. Wireless networking greatly enhances the utility of portable computing device. It allows mobile users versatile communication with other people and expedient notification of important events, yet with much more flexibility that with cellular phones or pagers. It also permits continuous access to the services and resources of land-based networks. The combination of networking and mobility will engender new applications and services, such as collaborative software to support impromptu meetings, electronic bulletin boards whose contents adapt to the current viewers, lighting and heating that adjust to the needs of those present, and navigation software to guide users in unfamiliar places and on tour [M. Weiser (1993)]. Database in a wireless world is an interesting area of work because as the computing migrates away from the desktop & mainframes towards mobile devices, it becomes necessary to manage data on numerous PDA’s Cell Phone & other mobile devices. The problem is that data management in these environments requires storage, retrial, updates and synchronization of information that is dispersed across multitudes of mobile as well as immobile computing devices-large & small. Mobile devices like PDA, Table PC, Laptop, Notebook, Multimedia Mobile phones and other portable devices are gaining popularity and being used day by day. These devices have mobile applications with databases which help in many ways according to their need. Besides maintaining the timing constraints, the database needs to follow the consistency constraints [Imieĺinski, (1993)]. For this, different transaction concurrency control algorithms & protocols have been proposed to satisfy these constraints in wire network. But the problems become more complicated in Mobile Distributed Real Time Database System (MDRTDS), where a database is partitioned into a number of smaller distributed databases as well as local database spreading at different location. The database technology allows users using handheld devices to link to their corporate networks, download data, work offline, and then connect to the network again to synchronize with the corporate database. For example, with a mobile database embedded in a handheld device, a package delivery worker can collect signatures after each delivery and send the information to a corporate database at day's end [Andreas, (1996), Imielinski (1994)]. When implementing a wireless LAN, the concepts generally associated with network management come into a whole new light. With a traditional wired LAN, most network management can be done through configuration of switches, routers, and the layout of the physical cable plant. Monitoring takes place through management tools that watch the network through the devices and statistics or network- related information can be gathered through these tools. In a wireless LAN, it has been difficult to port these types of management tools and procedures over to a whole new network infrastructure. Most of the existing tools are not designed to handle wireless LAN and the tools that are designed for wired LAN are not necessarily designed to interface well with existing network tools. This has led to difficulty in wireless LAN being adopted into corporate environments where network management is a critical and necessary part of daily operations. As the wireless technologies improve, more and more tools are becoming available to integrate wireless LAN into an existing wired LAN infrastructure. Obviously, one of these tools is the Cisco Wireless-Aware LAN. The important point to remember is that wireless technologies evolve almost daily and as time goes on, the integration of wireless LAN and wired LANs will become easier to administer and control. The complete access and management of information has been one of the driving forces in the evolution of computer technology. Central computing gave the ability to perform large and complex computations and advanced information manipulation. Advances in networking connected computers together and led to distributed computing. Web technology and the Internet went even further to provide hyper-linked information

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access and global computing. However, restricting access stations to physical locations limits the boundary of the vision. The real global network can be achieved only via the ability to compute and access information from anywhere and anytime.This is the fundamental wish that motivates mobile computing. This evolution is the cumulative result of both hardware and software advances at various levels motivated by tangible application needs. Infrastructure research on communications and networking is essential for realizing wireless systems. Equally important is the design and implementation of data management applications for these systems, a task directly affected by the characteristics of the wireless medium and the resulting mobility of data resources and computation. Although a relatively new area, mobile data management has provoked a proliferation of research efforts motivated both by a great market potential and by many challenging research problems. Data Management for Mobile Computing provides a single source for researchers and practitioners who want to keep abreast of the latest innovations in the field. It can also serve as a textbook for an advanced course on mobile computing or as a companion text for a variety of courses including courses on distributed systems, database management, transaction management, operating or file systems, information retrieval or dissemination, and web computing [Pitoura , (1993)]. Other issue relating to mobile computing is the energy (battery power). One way is to improve hardware power efficiency, a key concern of every designer of mobile hardware. One more is to make software energy-aware, thereby reducing its energy demands on hardware. It is a scarce resource for mobile computers. This limitation influences many aspects of system design. Can we reduce the requirements of data transfer for the sake of energy efficiency? Yes, by doing scheduled data broadcasts, we may reduce the need for mobile systems to transmit queries. But on the other side it will increase the amount of data residing on machines administered by users, rather than by database administrators. In addition, these machines may, at times, be disconnected from the network; thus, raising the question about the consistency of data [Rakotonirainy, (1999), Pitoura (1993), Zaslavsky (1998)]. Constraints of Mobility includes first mobile devices are resource wise poor relative to fixed devices, secondly mobility is inherently hazardous, thirdly mobile connectivity is highly variable in performance and reliability and lastly mobile devices rely on a finite energy source [Flinn, (1999), Siau (2003)]. These constraints are not artifact of lying technology but are essential to mobility. They altogether make the mobile system more complex and complicated thus it requires to rethink these lying approaches to information access. Caching plays a vital role in mobile computing because of its ability to alleviate the performance and availability limitations of weak-connected and disconnected operation. But evaluating alternative caching strategies for mobile computing is problematic. It raises some questions as what is an appropriate set of caching metrics for mobile computing. Under what circumstances does one use metric? How does one efficiently monitor these metrics? What are the implications of these alternative metrics for caching algorithms? As one of the major cost involved in wireless communication, the connectivity cost, is paid for on the basis of connection time, there is an incentive for certain mobile hosts to be disconnected for substantial periods. However, during the time of disconnection, the user may still be working on the host machine and may issue queries and updates on data on locally cached data. This situation creates several problems recoverability & consistency [Siau, (2001), Johnson (1998)]. Updates entered at the mobile host machine which is not connected may be lost if the machine undergoes a major failure. This problem will result from the fact that only copy of information is kept at local host and simulation of storage that takes care of failure will be difficult to do. The locally cached data may become inconsistent, but the mobile host can discover this fact only when it is reconnected. Similarly, the updates occurring in the mobile host cannot be propagated until reconnection occurs. However, such updates must be propagated as and when the mobile host reconnects. However, if the mobile host caches read-only copies of data, which is being updated by other computers, the cached data may become inconsistent once a different machine updates the value. In such cases on reconnection, the mobile host may be sent with invalidation reports that may inform it about inconsistent cache entries. Two increasingly common approaches to providing data availability are the storage area network (SAN) and network-attached storage (NAS). Data availability can be measured in terms of how often the data is available and how much data can flow at a time. The emergence of powerful portable computers, along with advances in wireless communication technologies, has made mobile computing a reality. Among the applications that are finding their way to the market of mobile computing those that involve data management hold a prominent position. In the past few years, there has been a tremendous surge of research in the area of data management in mobile computing. This research has produced interesting results in areas such as data dissemination over limited bandwidth channels, location-dependent querying of data, and advanced interfaces for mobile computers [Ed. Van Sickle (2007), Badrinath (1998)]. This paper is an effort to survey these techniques and to classify this research in a few broad areas.

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The mobile-computing environment consists of mobile computers, which are referred to as mobile hosts, and a wired network of computers. The communication between the Mobile hosts and the wired network takes place through the computers referred to as mobile support stations. A mobile support station manages the mobile hosts within its cell. But what is a cell? A cell is defined as the geographical area covered by a mobile support station. Mobile hosts may move between cells, thus, necessitating a transfer of control from one mobile support station to another. Since mobile hosts may, at times, be powered down, a host may leave one cell and rematerialize later at some distant cell. Therefore, moves between cells are not necessarily between adjacent cells. Within a small area, such as a building, Mobile hosts may be connected by a wireless local-area network within a small area, which may provide lower-cost connectivity than a wide-area cellular network. This will also reduce the overhead of transfer of control. It is possible for mobile hosts to communicate directly without the intervention of a mobile support station. However, such communication can occur only between the nearby hosts. The size and power limitations of many mobile computers have led to alterative memory hierarchies. Flash memories may be used in such systems to save power. If the mobile host includes a hard disk, the disk may be allowed to spin down when it is not in use, to save energy. Issue relating to wireless computing is that creates a situation where machines no longer have fixed locations and network addresses. This may complicate query processing for the cases where location plays a key role, since it becomes difficult to determine the optimal location at which to materialize the result of a query. This may happen only for the cases where the location of the user is a parameter of the query. For example, if a traveler information system provides data on hotels, roadside services, etc. to motorists; queries about services that are ahead on the current route must be processed based on knowledge of the user's location, direction of motion, and speed. Location-dependent information: Because traditional computers do not move, information that depends on location, such as the local name server, available printers, and the time zone, is typically configured statically. One challenge for mobile computing is to factor out this information intelligently and provide mechanisms for obtaining configuration data appropriate to each location. Additionally, a mobile computer carried with a user is likely to be used in a wide variety of administrative domains. Dealing with the multitude of conventions that current computing systems rely on is another challenge to building mobile systems. Besides this dynamic configuration problem, mobile computers need access to more location-sensitive information than stationary computers do. The challenge for mobile computing is to allow more flexible access to this information without violating privacy. Legitimate uses of location information include contacting colleagues, routing telephone calls, logging meetings in personal diaries, and tailoring the content of electronic announcement displays to the Migrating locality. Mobile computing engenders a new kind of locality that migrates as users move. Even if a mobile computer is equipped to find the nearest server for a given service, over time migration may alter this condition. Because the physical distance between two points does not necessarily reflect the network distance, the communication path can grow disproportionately to actual movement. For example, a small movement can result in a much longer path when crossing network administrative boundaries, and a longer network path means Mobile computers need access to more location-sensitive information than do stationary computers. Communication traverses more intermediaries, resulting in longer latency and greater risk of disconnection. A longer communication path also consumes more network capacity, even though the bandwidth between the mobile unit and the server may not degrade. To avoid these disadvantages, service connections may be dynamically transferred to servers that are closer.9 When many mobile units converge, during meetings, for example, load-balancing concerns may outweigh the importance of communication locality. Another source of problems is the cost of resolving data conflicts. In DRTDBS, different real time concurrency control protocols have been proposed. One of the commonest methods to resolve data conflicts between transactions with different priorities is by restarting transactions. How ever this will be very expensive under a mobile environment The restarted transactions will have a very probability of deadline missing. Methods have to be design to reduce the cost in resolving the conflict. To reduce the number of restarts is a solution to improve and deduce the conflict of data by serializability.

3. Routing and Query Processing The mobile computing poses typical problems from the point of view of routing and query processing. For example, as per the mobile-computing model, the route between a pair of hosts may change over time, if one of the two hosts is mobile. This simple fact may have a dramatic effect at the network level, since location-based network addresses are no longer constants within the system. However, these networking issues are beyond the scope of this course.

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The mobile-computing model also directly affects database query processing. In the case of distributed query processing, the communication costs play important role in query optimization process while selecting the best method of query evaluation strategy [Madria (1998)]. Mobility results in dynamically changing communication costs, therefore, complicate the optimization process. User time is a highly valuable commodity in most of the business applications. Connection time is the unit of monetary charges is assigned in most cellular systems; therefore, it should be minimum. One of the basic principles of radio communication is that it requires less energy to receive than to transmit radio signals [Dunham (1998)] thus, transmission and reception of data impose different power demands on the mobile host.

4. Mobile Distributed Real Time DBS Issues Transparency issues (DDBS should appear as a single system) Distributed Database Design (fragmentation, allocation, and replication) Distributed Query Processing Distributed Query Processing: For centralized DBSs, the primary criteria for measuring the cost of a query evolution strategy is the number of disk accesses (# blocks read /written). For distributed databases, additionally the (1) cost of data transmission over the network and the (2) potential gain in performance from having several sites processing parts of the query in parallel must be taken into account [ Dr. Michael (2003)].

Distribution Design Issues

Why fragment at all? Can't we just distribute relations? What is a reasonable unit of distribution? Fragmentation techniques and how much to fragment? How to test correctness? How to allocate fragments on the different sites? Why and how to replicate fragments? The importance of information and data management has been highlighted by many authors; the review is an important one outlining the key issues of information systems research.

5. Broadcast Data It is often desirable for frequently requested data to be broadcast in a continuous cycle by mobile support stations, rather than transmitted to mobile hosts on demand. A typical application of broadcast data is stockmarket price information. There are two reasons for using broadcast data: The mobile host does not have to invest on the energy cost for transmitting data requests The broadcast data can be received by a large number of mobile hosts in a single transmission, at no extra cost, thus, ensures effective utilization of the available transmission bandwidth. Thus, the mobile hosts need to only receive data as and when those data are transmitted, rather than consuming energy by transmitting a request. The mobile host may also have the local non-volatile storage for storing (cache) the broadcast data as and when received, for possible later use. The mobile host may optimize energy costs by determining whether a given query may be processed using only cached data. In case, the cached data is not found to be appropriate for the query, then the mobile host may either wait for the data to be broadcast, or transmit a request for data. However, in order to make this decision, the mobile host must know when the relevant data will be broadcast. The broadcasting of data may be made according to a fixed schedule or a changeable schedule. If the schedule of data transmission is fixed then the mobile host uses the known fixed schedule to determine when the relevant data will be transmitted. In the data transmission, schedule is

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changeable then even the broadcast schedule may itself be broadcast at a well-known frequency and time intervals. In effect, the broadcast medium can be thought of as a disk with a high latency Requests for data can be thought of as being serviced when the requested data are broadcast. The transmission schedules behave like indices on the disk. This area is still evolving and research is still being conducted on broadcast data issues.

6. Securities issues in MDRTS Mobile computing with networked information systems help increase productivity and operational efficiency. This however, comes at a price. Mobile computing with networked information systems increases the risks for sensitive information supporting critical functions in the organization which are open to attacks. This chapter discusses different techniques to secure information over mobile computing environments. Recent years have witnessed the rapid growth of mobile computing environments. One of the major concerns in such environments is security, specially in the context of wireless communications. We describe some of the important issues which need to be addressed in designing a security scheme for mobile communications. These include autonomy of communicating entities, mobility of the users, limitations of the hardware, etc. We describe a scheme which addresses the above issues, and provides a correct and efficient mechanism to establish secure communications. Our scheme provides authentication of the communicating entities, location privacy, and secure messaging [V. Bharghavan , (1995)]. Making computers portable increase the risk of physical damage, unauthorized access, loss, and theft. Breaches of privacy or total loss of data become more likely. These risks can be reduced by minimizing the essential data kept on board. Obviously, a mobile device that serves only as a portable terminal is less prone to data loss than a stand-alone computer. Low power Batteries are the largest single source of weight in a portable computer. While reducing battery weight is important, too small a battery can undermine the value of portability by causing users to recharge frequently, carry spare batteries, or use their mobile computers less. Minimizing power consumption can improve portability by reducing battery weight and lengthening the life of a charge. Thus reducing the power consumption with low weight devices should be invented to populate the mobile computing. This is the largest challenge for researchers that as the weight and size are reducing the charging problems with squat battery life increases. Small capacity, Storage space on a portable computer is limited by physical size and power requirements. Traditionally, disks provide large amounts of non-volatile storage. In a mobile computer, however, disk drives are a liability. They consume more power than memory chips, except when off line, and they may not really be non-volatile when subject to the indelicate treatment a portable device receives. Hence, none of the PDA products have disk drives. Coping with limited storage is not a new problem. Solutions include compressing files automatically, accessing remote storage over the network, sharing code libraries, and compressing virtual memory pages. Although today's networked computers have had great success with distributed file systems and remote paging, mobile computers that regularly encounter network disconnections are less capable of relying on a network. A novel approach to reducing the size of program code is to interpret script languages instead of executing compiled object codes, which are typically many times larger than the source code. This approach is embodied by General Magic's Tele-script and Apple Technology Group's Dylan and Newton-Script. An equally important goal of such languages is to enhance portability by supporting a common programming model across different machines. Mobile computing is a technology that enables access to digital resources at any time, from any location. From a narrow viewpoint, mobile computing represents a convenient addition to wire-based local area distributed systems. Taken more broadly, mobile computing represents the elimination of time-and-place restrictions imposed by desktop computers and wired networks. In forecasting the impact of mobile technology, we would do well to observe recent trends in the use of the wired infrastructure, in particular, the Internet. In the past year, the advent of convenient mechanisms for browsing Internet resources has engendered an explosive growth in the use of those resources. The ability to access them at all times through mobile computing will allow their use to be integrated into all aspects of life and will accelerate the demand for network services. The challenge for computing designers is to adapt the system structures that have worked well for traditional computing so that mobile computing can be integrated as well. The second and more challenging aim was to determine where existing solutions can be applied, where mobility raises truly new challenges, and which of these challenges are there to last. Of course, these discussions were to take into consideration not only general solutions from the database community at large, but also the approaches that have been developed by the mobile databases community over the last decade, e.g.: Moving objects and mobile users

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Mobile data dissemination and delivery Mobile data replication and synchronization Discovery and composition of mobile services Mobility awareness and adaptability Location-dependent, context-based querying and optimization Designing location-aware, context-aware services Mobile sensor and stream data management Continuous querying Self-organizing, self-tuning mobile components Ad-hoc processes and networks Mobile transactional processing Quality of Service for mobile databases Low power cryptography and other cryptographic solutions designed for wireless networks Methods of identifying, authenticating, and safely integrating mobile devices into a network

7. Software Models To deal with the characteristics of mobile computing, especially with wireless connectivity and small devices, various extensions of the client/server model have been proposed. Such extensions advocate the use of proxies or middleware components. Proxies of the mobile host residing at the fixed network, called server-side proxies, perform various optimizations to alleviate the effects of wireless connectivity such as message compression and re-ordering. Server-side proxies may also perform computations in lieu of their mobile client. Proxies at the mobile client undertake the part of the client protocol that relates to mobile computing thus providing transparent adaptation to mobility. They also support client caching and communication optimizations for the messages sent from the client to the fixed server. Finally, mobile agents have been used with client/server models and their extensions. Such agents are initiated at the mobile host, launched at the fixed network to perform a specified task, and return to the mobile host with the results. The emergence of powerful portable computers, along with advances in wireless communication technologies, has made mobile computing a reality. Among the applications that are finding their way to the market of mobile computing—those that involve data management—hold a prominent position. In the past few years, there has been a tremendous surge of research in the area of data management in mobile computing. This research has produced interesting results in areas such as data dissemination over limited bandwidth channels, location-dependent querying of data, and advanced interfaces for mobile computers. This paper is an effort to survey these techniques and to classify this research in a few broad areas [D. Barbara (1999)]. Another concern in terms of software architectures is adaptability. The mobile environment is a dynamically changing one. Connectivity conditions vary from total disconnections to full connectivity. The resources available to mobile computers are not static either, for instance a “docked” mobile computer may have access to a larger display or memory. Furthermore, the location of mobile elements changes and so does the network configuration and the center of computational activity. Thus, a mobile system is presented with resources of varying number and quality. Consequently, a desired property of software systems for mobile computing is their ability to adapt to the constantly changing environmental conditions. Today, the success of data services used from small mobile devices, like digital phones or PDAs, appears very limited. Different reasons can be identified, which prevent the average customer from broadly using wireless data services. At first, the user has to deal with very uncomfortable devices in terms of UI ergonomic, and on the other hand, the costs for wireless data communication are extremely high. These restrictions can be overcome by employing a system concept, which is built up on two main components: personalized display software allows simplifying the information access on the wireless terminal, while an intermediate agent residing on the Internet takes care of mining the desired contents from the open Web. In addition to the improved UI handling, this concept offers a reduction of access costs and an increase in retrieval speed. Realworld experiments with an information system on actual train departures are reported for measuring and demonstrating the benefit of the described system concept [Y. Villate, (1998)].

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Wireless mobile computing breaks the stationary barrier and allows users to compute and access information from anywhere and at anytime. However, this new freedom of movement does not come without new challenges. The mobile computing environment is constrained in many ways. Mobile elements are resourcepoor and unreliable. Their network connectivity is often achieved through low-bandwidth wireless links. Furthermore, connectivity is frequently lost for variant periods of time. The difficulties raised by these constraints are compounded by mobility that induces variability in the availability of both communication and computational resources. These severe restrictions have a great impact on the design and structure of mobile computing applications and motivate the development of new software models. To this end, a number of extensions to the traditional distributed system architectures have been proposed. New software models, however, are static and require a priori set up and configuration. This in effect limits their potential in dynamically serving the mobile client; the client cannot access a site at which an appropriate model is not configured in advance. The contribution of this paper is twofold. First, the paper shows how an implementation of the proposed models using mobile agents eliminates this limitation and enhances the utilization of the models. Second, new frameworks for Web-based distributed access to databases are proposed and implemented [J. Rodriguez, (2002)]. The technical challenges that mobile computing must surmount to achieve this potential are hardly trivial, however. Some of the challenges in designing software for mobile computing systems are quite different from those involved in the design of software for today’s stationary networked systems. In this paper we focus on the issues pertinent to software designers without delving into the lower level details of the hardware realization of mobile computers.

8. Conclusions Mobile distributed database are being gradually more used in various business, supported by availability of various distributed database management system softwares products. This is a big issue that how the data is mange using mobile distributed management system by minimizing the cost and performance of the business. The Mobility brings in a novel dimension to the existing solutions to the problems in distributed databases. We have surveyed a number of the problems and existing solutions. We have identified upcoming research areas that, due to the nature and constraints of mobile computing environment, need rethinking. The upcoming research directions discussed here will be the centers of attractions among the mobile database researchers in future. The key research issues that the research community has tried to tackle are how to cope with mobility, frequent disconnection and energy limitation of the client in a number of DBMS issues, such as transaction management, data caching, data replication and location-aware query processing [P. Serrano-Alvarado, (2004)]. Additional work is also found in the areas of security and privacy [G. Bernard, (2004)], especially for detecting malicious transactions and preserving privacy in location-aware queries. Performance in distributed database is heavily dependent on allocation of data among the sites of the database. The static allocation provides only limited response to workload changes. This situation is even worse when the mobile wireless computers are included in replication schema. Some new methods with their practical approach must be needed for successful mobile computing system. Mobile devices supporting wireless communication have become increasingly relevant in the development of multi-agent systems. They provide a framework for obtaining ubiquitous communication and building applications for mobile environments. Mobile agents present very interesting advantages over the traditional client/server approach in a wireless context. In this chapter, the advantages of mobile agents have been presented and mobile agent platforms have been studied. To conclude, a discussion about the future of mobile agents is established. Some issues need to be resolved to enable adoption multi-agent systems to develop Ambient Intelligence applications [ Estefanía, (2007)]. References [1] [2]

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