2015 International Conference on Smart Sensors and Application (ICSSA)
Optimal Design of Wireless Sensor Network for Providing Qos Sathyaprakash Palaniappan, Prakasam, Jayakumar Vaithiyashankar, Dr. Shohel Sayeed Department of Computer Science Engineering, Mahabarathi Engineering College, Chinnasalem, India Department of Electronics and Communication, United Institute of Technology, Coimbatore, India Faculty of Information Science and Technology (FIST), Multimedia University, Melaka, Malaysia.
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[email protected] Abstract—With respect to the increase in demand of wireless sensor network in various real time Application. We present WISEN algorithm which is specially designed for WSN providing multiple communication architecture and mechanism to improve the Quality of service and routing performance. WISEN focuses on functions such as node synchronization, node localization for improving QoS. The design of WISEN algorithm evaluated through network simulator with various protocols proves better performance in terms of packet loss, throughput and delay metrics. Collectively design of WISEN assumed optimal for Researchers.
II. RELATED WORKS A. Literature Review Eminent research works being carried out as literature survey [9], which had suggested end-to-end QoS support using differentiated service approach using various mechanisms and algorithms among variable protocol layers, and hence maximizing bandwidth utilization and resource management. TABLE I.
Type of Protocol
Keywords—Wireless sensor network, QoS, Sensor design, Throughput, End-to-End delay, inter arrival time.
Data-centric Protocols
I. INTRODUCTION
Location Aware Protocols
Wireless sensor networks [1] are widely used in all engineering fields such as energy-saving smart grid, intelligent buildings, smart home, forest fire detection, earthquake monitoring, preventive maintenance, medicine & health care , Telematics , Biodiversity mapping logistics, precision agriculture. It can be deployed for replacing human being from hazardous and dangerous places like radioactive zone, volcanic region. The WSN can be deployed for monitoring, sensing and alarming the particular event. WSN having lot of issues to be solved while implementing in real time Applications. Namely depletion of energy source, complex routing, vulnerable to security attacks, Compressing techniques, QoS etc. Quality of service an important issue that need to be improved and should be addressed effectively [2].
Scheme Name SPIN, Directed Diffusion, Rumor Routing, COUGAR, ACQUIRE, EAD MECN, SMECN, GAF, GEAR, Span, TBF, BVGF
Heterogeneity-based Protocols
CADR, CHR, IDSQ
Hierarchical Protocols
LEACH, PEGASIS, HEED, TEEN, APTEEN
QoS specific protocols
SAR, SPEED
Mobility Protocols
routing
SEAD, TTDD, Data MULES, Dynamic Proxy Tree-Base Data Dissemination
An in-depth survey [10] [11] and review [12] is carried out to analyze the existing effective WSN routing protocols (Table I), which focus on establishing multiple routing paths and node route analysis. Dazhii et al. [13] work support QoS in WSN as well analyzes QoS requirements imposed by the major applications of WSN. The analysis shows that intensive research has been conducted on data aggregation routing, but MAC layer retransmission issue has not been addressed.
Wireless sensor network are complicated in terms of design, low processing capacity, limited power supply, less memory capacity. According to that energy consumption will be minimized. Micro controller processing will be simple. EPROM of the micro controller will be effectively handled To guarantee the quality of QoS parameters WISEN adopts both single hop and multi-hop Communication. QoS [4] [5] parameters like throughput , Inter arrival time and End to end delay are better than popular energy efficient algorithm like LEACH [6], SPIN [7] and other similar algorithms .WISEN has multiple advantages where the test bed has been implemented with ns-2 [7] simulator using sense 3.0 module. The QoS performance of WISEN is observed to improve in throughput and end to end delay.
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TYPE OF PROTOCOLS
Krishnamachari [14], work on WSN routing based on aggregation heuristics, called Shortest Paths Tree (SPT), Center at Nearest Source (CNS). The result of SPT and CNS is found to be similar with AODV protocol [15], the functionality of these schemes was effective in terms of data loss and path establishment.
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2015 International Conference on Smart Sensors and Application (ICSSA)
Lin et al[16], discussed on energy consumption tradeoffs between the data aggregation and retransmission in wireless sensor network by using the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) MAC protocol is discussed. But, the energy consumption frame work does not discuss about the power consumption in idle mode which make the proposed algorithm to fail in identifying an energy efficient data aggregation tree. In addition, retransmission latency is not considered in this work; hence that it does not guarantee the delay QoS.
between nodes is carried out by cluster heads rather than all sensor nodes. Optimal number of cluster heads is estimated to be 5% of the total number of nodes. III. PROBLEM ANALYSIS The literature survey shows that important problem is quality of service with respect to low cost design. The routing performance is the main parameter for efficient protocol which leads to better quality of service but not effectively addressed. Node synchronization and localization will affects the delay in communication results that throughput of the sensor network which is directly affects the Quality of service. Because of these reasons the above said problems Needs to consider while design WSN. To achieve guaranteed QoS parameters we are going to introduce minimal activities in Wsn operating procedure and enable plug play features. In order to improve the throughput we need an optimal design of WSN Algorithm. For that we propose a new design in this paper WISEN.
Ian.F.Akyildiz et al [8] work discusses on good survey of routing protocols on sensor networks. The paper suggests different protocols, where flooding is an algorithm that relays message from the source node to all other nodes in the network. The main drawback of flooding is redundancy of messages, complexity and it is not energy aware. Gossiping is another proposed algorithm to overcome the drawbacks of flooding. Here the node selects one of its neighbor nodes and sends the data to that particular node and this process continues until the message reaches the destination node, hence the redundancy and complexity decreases.
While designing an algorithm optimal node synchronization and localization procedure will be taken into account. It consumes more energy and huge process time which leads to complex execution procedure.
PASCAL is proposed [17] with implementation of leveling, sectoring and clustering methods. The routing algorithm considers WSN nodes to be static or have a very low mobility with respect to signal propagation. In this algorithm, the packets are forwarded by flooding. The concept of node switching introduced in PEGASIS [18] helps to improve the lifetime of the sensor network. Abdelzaher et al, [19] work on Directional Source Aware Protocol (DSAP) focuses on WSNs routing protocol. This protocol is a local information routing protocol, where each node maintains its neighbor's information. Similarly each node will transmit a packet to its known neighbor, which is closer to the destination. This process continues, until the packet reaches the destination. Directional Value (DV) parameter is used to choose a neighbor node to forward the packet.
It is necessary to know the location of the sensor and where the information is coming from. The node localization is the technique to identify and recognize the location of the particular sensor with the minimal network cost. In some applications, it requires the higher accuracy of location identification while in some other applications positioning not need and impractical one. While designing the sensor network it is important to consider node localization in order to get entire knowledge of the environment and where it is located Localization technique: Localization in wireless sensor network defined as act of identifying position of sensor node in sensor network. Localization is one key parameters in wireless sensor network. Accuracy of localization is highly expected because it is the geographical location sensor node in the network. Localization are two types 1) know location means target source localization. 2) If the position of the node is unknown means node self-localization.
SPIN [7] (Sensor Protocols for Information via Negotiation) generates a data-centric routing mechanism, which adopts naming procedure for data using high level descriptors or meta-data. During transmission, SPIN uses sensor meta-data to be exchanged between sensors through data advertisement mechanism in order to select the route for transmission. This approach solves the issues of flooding such as redundant information passing, overlapping of sensing areas and resource blindness and improves energy efficiency.
Node synchronization is also another parameter, which is based on the message exchange among sensor nodes. Most of the synchronization protocols are Network wide synchronization based . Contrasting to that pair wise synchronization leads to adjust the clock of the whole nodes present in the network. this will minimize the delay while time stamping event .
Shuo Deng et al. [20] adopt a set of sub-optimal paths occasionally to increase the lifetime of the network. These paths are chosen by means of a probability function, which depends on the energy consumption of each path. This approach argues that the usage of the minimum energy path all the time will deplete the energy of nodes on that path, while multiple paths is used with a certain probability so that the whole network lifetime increases.
IV. DESIGN ISSUES Latest advancement in the wireless sensor network domain leads us to open research questions and becomes challenging for network analysts and designers. Normally there are three ways to analyze and measure the performance of wireless sensor networks using 1) analytical methods, 2) computer simulation and 3) direct measurement. During the direct measurement, the unsolved research problems such as energy depletion, decentralization issues, fault tolerance nature, complex routing algorithms makes it difficult to measure
Low-Energy Adaptive Clustering Hierarchy (LEACH) [6] adopts hierarchical routing algorithms which forms clusters of the sensor nodes based on its received signal strength and utilization of local cluster heads as routers to the sink. This approach consumes less energy since the transmissions
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physically. Hence simulation is the only possibility to quantitative measurement of WSN and better than the direct measurement method. Ns-2 is the most widely used simulator tool by the research community to design, analyze and measure performance metrics of both wired and wireless networks.
communication pattern results in reduced QoS as well degrades the network lifetime. Optimal route selection leads to selection of short routes thus makes WISEN to consume low energy during route selection process. Hence this work focuses on end-to-end channel awareness and end-to-end channel quality in terms of path lifetimes.
Even though ns-2 is an object oriented design, unnecessary interdependency between each modules by binding functionalities with strong types makes tedious implementation for new sensor modules. Ns-2 is not sufficient for real-time WSN output validation. There forth SENSE 3.0 is emulator which uses the libraries of ns-2 which supports extended features such as extensibility, re-usability and scalability.
V. PERFORMANCE AND METRICS With respect to the performance evaluation the following QoS metrics are measured 1) Throughput: Throughput is defined as the number packets received per unit time. Hence the more number of packets received with minimal packet loss considered as better quality of the protocol.
WISEN adopts the following design goals: (a) Low Cost (b) Improved Communication (c) Minimal Latency (d) Better Throughput A Low Cost To incorporate the phenomenon of low cost and deployment WISEN uses simple PIC 18F/16F micro controller which embeds within it minimal memory of 256 kb EPROM. The micro controller controls various I/O ports which connect to various sensor components to collect data working in dynamic environment. Data gathered from multiple sensors can be transmitted through Zigbee communication device and stored in standard storage device as a file.
ThroughPut=
2) Time interval : Time interval is defined as the exchange of time information about the particular interval period. This time interval is useful in the time synchronization in the sensor network. Hence time interval should be very low for the better and efficient time synchronization also probably within few milli seconds. Time Interval= t 2− t 1
Where t1 = current Timestamp, t2 = Previous Timestamp
Major processing capabilities are limited in WISEN which avoids the cumbersome and time-consuming issues behind setup and conduct of an experiment in variable environments. The primary aim of developing this test bed is to design and implement a Wireless sensor network, which involves multiple sensors with minimal cost and complexity in understanding as well implementing the QoS variable nature of WSN network over an IEEE 802.15.4 Zig bee communication network. ZigBee technology [20] is used among research industry as a popular wireless standard, which implements the monitoring and managing packet loss and throughput of system. Collectively this results in low cost design
3) End to End Delay: It is defined as time taken by a packet sent from source to destination. This delay due to some physical or some other intermediate communication process involved. The end to end delay preferred to be low for a communication protocol. End to End queuing delay of a path:
T E=
∑
TQ RT
(i)
i Path
Where Te- end to end delay i` - sensor node TQ - total queuing delay RT - real time traffic 4) Inter arrival time: The packets arrival time is the number of packets arrived per unit time. On contrast the inter arrival time is the inverse of arrival time. Thus lesser inter arrival rate will automatically increase the throughput of the network.
B Improved Communication WISEN identifies its neighbors based on signal strength [10], the stabilized route is established over nodes on mobility based on ad hoc query approaches of requests and replies. Each forwarding node is bounded to another forwarding node, which helps in organized and scheduled session management and transmission data. Due to optimal routing procedure based upon bandwidth in use and link status of nodes in WISEN algorithm shows improved communication than compared algorithms
Inter Arrival Time=
C Minimal latency And Better throughput
1 Packet Arrival Time
A. Simulation Settings: Our simulation environment comprised of 300 ft. deployed with 30 nodes randomly distributed in the field. All the nodes are within 25 ft. communication range, where the source node present at the left side of the room and sink before the entrance of the room. Mean delay between the packets 15 ms. The table II shows the simulation properties.
WISEN algorithm keeps anvil of energy consumption of all nodes in transmission within its domain range, since any failure of a node due to less energy node may lead to loss of data. Selection of a node with less energy may lead to link or node failure such that reconfiguration of the network and recomputation of the routing paths, route selection in each
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Transmitted Packets− packet loss Tranmission duration
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2015 International Conference on Smart Sensors and Application (ICSSA)
TABLE II.
Type Channel
Radio Propagation Model
Two ray ground
Network Interface
Physical / Wireless Phy
MAC
IEEE 802_15_4
Interface Queue
DropTail/PriQueue
Antenna
OmniAntenna
LinkLayer
LL
Interface Queue Length
Simulation Time
50 SPIN/ LEACH/ PEGASIS/ WISEN 1000s
No of nodes
30
Area
300 ft
Routing Protocol
Fig. 1.
each node is determined by the duration of the experiment. The traffic generated suggests that the basic performance properties of the node uses CBR traffic model.
SIMULATION PROPERTIES Properties Wireless
VI RESULTS AND DISCUSSION
The performance of WISEN routing algorithm can be compared with existing traditional WSN routing algorithms using ns-2, simulator. WISEN outperforms SPIN significantly in terms of routing load balancing and bandwidth overhead primarily in terms of low mobility (such as static or mobility within room) as well manages LEACH in terms of throughput over a large network (30 nodes). However, its performance deteriorates slowly when the number of nodes ‘n’ is increased and its bandwidth usage gets overloaded. Such issues attribute to the aggressive usage of source routing cache in node, as shown in Fig 1. It has to be noted that the default experimental settings are used in the traffic test, except the number of packets created per node varies in individual experiments. The experiment starts with generating 50 packets per node for each time interval, which equals to 250 packets in total in network. As time interval moves on the total number of packets created increases by 40% to 100 packets per node, such that 500 packets and finally number of packets created is increased by 120% to 200 packets per node, which is 1200 packets in total. The experiment results are shown in Fig 2 and Fig 3 which discusses on loss of data observed over simulated test run and end to end delay.
WISEN – Simulation Test run
B. Discovery of QoS Path During degradation of QoS discovery process, source node indicates this information to neighbor nodes, which supports in identifying the source to identify multiple routes to its destination. This enables the source node to switch to cached routes in case of route break, which significantly reduces the possibility to restart a route discovery process and completely over again. However, under stressful situations, the cached routes are considered as invalid status which thus reduces unnecessary delay and handles network traffic effectively.
Fig. 2.
Fig 2 shows the observed throughput over 30 nodes, where WISEN is compared with other schemes such as LEACH, SPIN and PEGASIS. WISEN scheme is observed to show an improved throughput with an average of 1200 bps of transmitted data whereas LEACH and SPIN shows an average of 810 bps and 1200 bps respectively. WISEN is able to show a higher performance due to the effective usage of cached routes.
C. Test Bed Experimentation Experimental test bed is carried out in two approaches, as a real time approach where five WSN nodes are adopted and using a simulation approach with ns-2 sensorsim patch using 30 nodes. In first set of experiments, the performance of WISEN with varying number of packets per source node is tested. Since each WISEN node creates new packet with a fixed sampling interval, the total number of packets created by
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Observed Throughput for 30 nodes
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[2] [3]
[4]
[5]
[6]
Fig. 3.
End to end delay [7]
Fig 3 demonstrates the delay observed over 30 WSN nodes using WISEN algorithm, being compared with LEACH and SPIN. The performance shows that WISEN shows a minimal delay in data transmission compared to other schemes. LEACH also performs similar to WISEN such that both the schemes adopt minimal retransmission and hence session maintenance. The optimal route selection makes WISEN becomes the energy efficient protocol.
[8] [9]
[10]
VII CONCLUSION In this paper we have exhibited that our WISEN protocol provides better quality of service, utilizing multi hop routing, optimal energy efficiency. The simulation shows that WISEN shows a minimal delay in data transmission compared to other schemes. LEACH (Hierarchical protocol) also performs similar to WISEN such that both the schemes adopt minimal retransmission and hence session maintenance. The proposed protocol designed for real time wireless sensor network to provide better throughput, minimal latency and optimal energy consumption.
[11]
[12]
[13]
Simulation shows that the performance of Proposed WISEN protocol under different circumstance compared with both Hierarchical and flat routing protocols. Results shows that our proposed protocol WISEN achieved low End to end delay, higher throughput and optimal energy consumption compared to LEACH, SPIN and PEGASIS.
[14]
[15]
The performance shows that WISEN shows a minimal delay in data transmission compared to other schemes. LEACH also performs similar to WISEN such that both the schemes adopt minimal transmission and hence session maintenance. From the above results we can provide optimal design for wireless sensor networks including components, algorithm, quality of service and operating procedure. This will be good option for economic researching community in all aspects.
[16]
[17]
[18]
As a future work, we are interested to design new wireless sensor nodes and analyze our proposed protocol in real time implementation. Also wants to conduct the experiments in both indoor and outdoor environments.
[1]
[19]
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2015 International Conference on Smart Sensors and Application (ICSSA)
Shuo Deng, Hari Balakrishnan,Traffic-Aware Techniques to Reduce 3G/LTE Wireless Energy Consumption ACM CoNEXT, Nice, France, December 2012. [21] ZigBee Alliance, “ZigBee Gateway Device Specification,” (075468r30ZB), Jul. 2010. [20]
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