Panayotis Kikiras et al: WIRELESS SENSOR NETWORKS: BUSINESS MODELS AND MARKET ISSUES
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Wireless Sensor Networks: Business Models and Market Issues Panayotis K. Kikiras 1, Dimitris K. Drakoulis2, Dimitris A. Dres3, Georgios I. Stamoulis4
Abstract— Networks of sensors are continuously gaining ground in all types of industry applications and are believed to be evolving in a way similar to the evolution of the first interconnected computer systems into what we call today the Internet. A heterogeneous infrastructure is thus about to emerge as a dense web of rich information sources that will transform the World Wide Web into what has been called the “Real World Web” (RWW). The authors hereby assimilate the impact of this transformation process, the actors involved, the operational and business models associated with it. Index Terms—Sensor Networks, Business Models, Real World Web, Charging Models.
I. INTRODUCTION The emergence of sensor networks’ infrastructures on a global scale, the richness of information that may be collected, as well as the opportunity to use special purpose tools, including data mining and geographical information systems among others, will augment the experience of today’s web browsing in both scale and quality. The vision is the transition of today’s “web browsing” paradigm to what may be termed as “world browsing”. This transition will be evolutionary and hopefully seamless; however the advances offered for all types of individual and social activities (access to information, education, provision of medical services to name the most important ones) will be noticeable even to the average user. While literature on the WSN is abundant of information concerning technical issues of WSN’s such as transmission, topology control, addressing and indeed routing, as well as application support (localization, security), there is an apparent lack in the area of the types of services and the application scenarios about to emerge, the appropriate models around which the business is expected to evolve as well as the way these services are expected to generate revenue for the Manuscript received March 31, 2007, revised at May 15 2007 and presented at June 14-15, 2007. 1 P. K. Kikiras is with the University of Thessaly, Volos (Argonafton and Filellinon, 38221 Volos, 24210 74000, e-mail:
[email protected]). 2 D. K. Drakoulis, is with Telesto Technologies, Athens (Imitou 62 Holargos 15561 Athens, Tel. +302106541942, e-mail:
[email protected]). 3 D. A. Dres is with Telesto Technologies, Athens (Imitou 62 Holargos 15561 Athens, Tel. +302106541942,e-mail:
[email protected]). 4 G. I. Stamoulis is with the University of Thessaly, Volos (Argonafton and Filellinon, 38221 Volos, 24210 74000, e-mail:
[email protected]).
1-4244-1233-1/07/$25.00 ©2007 IEEE.
provider. In the paper at hand, the authors attempt to identify and describe the main technological trends, research and exemplify services relevant to several different user categories whose needs are different; prioritization in the exploitation of information is also graded (e.g. premium users, public authorities, plain users). The organization of the paper is as follows. In Section 2 the architecture of a typical WSN deployment and the interactions on which the WSN operation is based is briefly presented. In Section 3 authors proceed by reviewing the impact of the emerging ubiquitous networking infrastructure to the way consumers and industrial players experience the services offered by the existing Internet infrastructure, which may be considered in the form of a “Real World Web” (RWW); RWW may be perceived as a space composed of smart objects and ambient intelligence that incorporates the contemporary WWW and relevant applications, however extends well beyond its current scope and reach [4]. Finally in Section 3, the role of each actor in the RWW value chain is presented while business and revenue models are proposed for the delivery of such services. II.WIRELESS SENSOR NETWORKS OPERATIONAL OUTLINE A. WSN Deployment Architecture and Interaction between Components Although the technology area of WSN enjoys coverage by scientific ([1],[5]) and technological articles (a comprehensive survey may be found in [3]), it is appropriate that prior to the presentation and classification of emerging and future applications that make use of sensor services one has to define the services themselves. Nevertheless any simple, generic definition of a WSN service (“provides readings of observed phenomenon values upon request” etc.) is generally not going to capture all possible operational scenarios, and thus in order to reach a representative service provision model, the generic architecture of a WSN and a model of the interactions that take place need first be examined. In the core of the "Real-World Web" one finds the selforganizing networks of cheap autonomous wireless sensors nodes. Wireless sensor networks or WSNs, combine the ability of sensing their physical environment, simple wireless communication, minimal processing and storage while operating autonomously for long time periods (sense, reason,
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communicate and act, in whatever order). Typical sensing tasks for such a device could be temperature, pressure, light, vibration, sound, radiation, mechanical properties of structural materials, etc. Among the main restrictions in the operation of the WSN nodes, the most notable ones with regard to this contribution are power and lack of operational agility: each node is assigned one or more sensorial tasks and once deployed may not change function or position (a restriction mainly attributed to cost and dimensions limitations). In most of the applications scenarios where a WSN is deployed there is a distinctive difference between the “nodes” that sense and produce data and the “sinks” which are data consumers; additionally in most cases, sinks are network’s gateways to the real world (as depicted in Figure 1). Generally one may divide the operation of a WSN in the following general steps: 1) Data relevant to one or several sensing stimuli (Temperature, Pressure, Vibration, Noise, Humidity, etc) are collected by each single sensor, 2) Data from the various sensors are aggregated or “converge-casted” to a single or multiple sinks. Data aggregation may be followed by “in-network” processing, whereby distributed processing or fusing of the sensor readings takes place. In general the interaction between sources and sinks, typically accords to one or more of the following interaction patterns.
3) As the data produced are eventually required to be utilized by systems outside the WSN, gateway systems need to be introduced, the latter being nodes that operate in compliance to the WSN protocol functionality, while they also serve as termination nodes for the external communication system to which they connect. 4) The abovementioned interaction paradigms are desirable to support the following properties: a) Decoupling in space – neither sender nor receiver need to know their partner, and b) Decoupling in time – “network’s response” not necessarily directly fired by “question”, asynchronous communication. B. WSN Service Usage In the quest to interconnect the deployed WSN’s with external communication networks and in turn integrate the resulting system with the global internet infrastructure, decisions need to be taken with regard to the architecture of the integration, as well as to the bridging between several different network protocols; both remain to a large degree, open issues. Several different approaches generally apply, each one dependent of the type and requirements of the application that the WSN is deployed for. Authors in [6] have identified the following WSN usage scenarios (figure 2): (a) A single WSN is utilized for the purposes of a single application (WSN-specific application). This is the case for most of the contemporary applications. (b) A single application uses more than one different WSNs. The application is responsible for dealing with the heterogeneity of produced data. (c) Different applications use several underlying WSNs in a unified manner by means of a middleware integration platform. The applications are agnostic of the underlying middleware implementations.
Fig. 1. Typical WSN application deployment.
a) Event detection: Nodes locally detect events (maybe jointly with nearby neighbors), then report these events to “interested” sinks b) Event classification: Classification takes place based on own measurements or in cooperation with neighboring nodes. c) Periodic measurement: Sensors report measurements at the following occurrences 1) according to a schedule programmed prior to deployment, 2) when triggered by an event, or 3) according to a hybrid scheme when either of the above conditions is satisfied. d) Function approximation: Sensor network sampling is selected so as to approximate a function of space and/or time, (e.g., temperature map). e) Edge detection: Determine boundaries (or other structures) in a function (see the case of “where is the zero degree border line?”). f) Tracking: Report (or at least track) position of an object under observation (the example of a sensor on a mountain sensing all climbers in its proximity).
Fig. 2. WSN Usage Models (adopted from [6]).
C. WSN Data Provision Models With regard to the types of applications and usage models presented earlier, we may observe the existence of at least four data provision models, respective to the way the information is processed. These are: (1) the publish / subscribe model which its main idea is that nodes can publish data under certain names, and data consumers can subscribe to updates of such named data. This model is implemented by a software bus (middleware) which stores subscriptions, and published data, utilizes names as filters, and has services that assure that subscribers are notified whenever values of named data changes (figure 3),
Panayotis Kikiras et al: WIRELESS SENSOR NETWORKS: BUSINESS MODELS AND MARKET ISSUES (2) the pull model which is mainly query-driven and userinitiated (“show me all ground humidity readings from the sensors deployed in my farm”), (3) the push model which is mainly event–driven (report whenever a certain condition is satisfied according to node’s programming), and (4) the hybrid model which is mainly a Grade of Service (GoS) driven, application specific approach (by this model the WSN needs to report according to the minimum requirements arising from a Service Level Agreement),
Fig. 3.The Publish /Subscribe Service Model
Differences especially among the “push” and the “pull” alternatives are apparent; however in the power-scarce WSN “economy”, the selection of the (system initiated) push - is a much cheaper option than the simple (user initiated) pullmodel. This distinction implies that at the application level, power-demanding queries for real-time data (relevant to the “pull” data model) would belong to “premium” service offerings, while “standard” or “free” services would only offer data collected from the most recent report available by the system. III.
RWW SERVICES AND THE WSN VALUE CHAIN
A. RWW Value Chain Members and Roles The enrichment of the internet with geographically specific and up-to-date information extracted from the ever increasing number of WSNs deployed worldwide will definitely lead to its transformation into a “ubiquitous internet”; its wealth of information is directly exploitable by existing and new client tools, promoting the user’s awareness of his environment, thus enhancing the World Wide Web into the Real World Web (RWW). Throughout the years of the Information Revolution that took place in the recent decades, information is a resource and in turn a product of high value for the majority of the economic domains and the cost of its acquisition is valued according to the resources consumed for its generation, its scarcity, its precision and its timeliness. The information may be directly generated or be the outcome of a production chain whose links each or cooperatively add value to the information received. The RWW value chain consists of at least the following roles: 1) The WSN (Infrastructure) Owner: This entity owns one or more deployed sensors networks, which provide data critical to specific aspects of the entity’s business activities. Some of the data gathered by the deployed WSNs can be served to users either directly or through Content and Service
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Providers. 2) Content Provider – Aggregator and / or Middleware Provider: This entity is the mediator between real data and end users. Content providers own the roles of collecting and or aggregating data collected by different deployed networks, in order to provide service providers and end users with processed data or entirely new content based on raw data (primarily the sensors’ readings). 3) Service Provider (Mobile Operator, Web Portal Owner, Data Publisher): This entity stands at the top of the value chain. It provides users with content compiled by the content providers. Service providers have the ability to serve content over different channels (fixed, mobile or wireless access communication systems, including GSM/GPRS/3G, WiFi or emerging WiMAX, among others) and according to various formats (HTTP, WAP or SMS messages) based on the users’ needs. 4) Third Trusted Parties: Those are members of the value chain who are offered access to information for regulatory purposes (so as to promote competition in the market) or because they are legally entitled to request such access (government or other agencies serving the public interest). 5) Users (including the Society as a whole): The users are the consumers of all types of information ranging from raw data to highly processed, geography-referred, visually enhanced information and services. Other actors in the service-chain and the respective valuechain may also exist, however we intentionally choose to emphasize on the ones which span across the different WSN usage models. Additionally we restrict the classification to the actors who indeed add value in the service provision chain, thus omitting Infrastructure Equipment Vendors, whose role is primarily to provide the equipment required for the WSN infrastructure owners, while in some cases they may also be responsible for the maintenance of the deployed equipment. In (figure 4) the WSN content flow diagram is depicted, where one may observe the cardinality of the relationships is either one-to-many or many-to-many.
Fig. 4. WSN Content Flow Diagram
IV. BUSINESS MODELS AND REVENUE GENERATION IN THE REAL WORLD WEB A. Business Models for the Real World Web Given the unique characteristics of the WSNs, RWW
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applications are expected to emerge and rapidly span across business domains, especially in cases where continuous visibility of all types of assets, as well as awareness of their identity, condition and position is highly valued. In the most primitive business model, the company is the exclusive producer as well as consumer of the information content generated, while it also owns the infrastructure. A relevant example (from Supply Chain Management) is the case where a company uses multiple sensor infrastructures to monitor the conditions throughout a product’s lifecycle, from the time of manufacture, right up to the time the product is consumed (and even after that to monitor the recycle process). Although this scenario seems to produce little value to the potential users of Real World Web, it shows the value of the capabilities offered by WSNs for improving operational efficiency. A variation of this model is when sensor networks are embedded in products, materials and buildings, to prove liability. However as the demand for services grows and the services themselves mature, one will see the expansion of the RWW market to support new needs and complex business relationships representative of the roles in the RWW value chain discussed in the previous part. In the following we draw attention to three (3) distinct business models, as well as representative business scenarios: 1) Asset Management Business Model. According to this model, companies or organizations use their own sensor infrastructure to acquire real-time or near real-time information, critical for their business, however allow other authorities (any type of Third Trusted Parties, who may also participate) to access all or part of the data collected. This would be the case in the agricultural domain, where the soil temperature and humidity is monitored by the farm owner in the case of a sensitive crop, while all or part of the measurements are also available to the local office for agriculture to gather info about potentially dangerous conditions such as icing. 2) Knowledge Management Business Model. A rather more complex model appears in the case that the content is aggregated from multiple sites, and then processed to be exploited for other (again mostly commercial) purposes. The content aggregator has no ownership over the diverse infrastructure and needs only to know the reliability of the measurements made. The number of applications falling within this category is very small today, however the immense penetration of sensors in numerous markets expected within a decade from today [2], creates numerous opportunities for “content aggregators” acquiring valuable information, relevant to consumer trends, buying preferences, or any other type of insight to the retail market, information of extreme value to future targeted marketing campaigns. This model represents the highest correlation with current WWW-based services and in this way offers the opportunity to exploit the momentum created from the success of commercially viable web services, towards the implementation of the RWW vision. 3) Public Services Business Model. Public entities will build their own infrastructure or acquire access to content generated by the infrastructure built by private organizations. The latter practice will especially apply when the investment
in the infrastructure is state-subsidized (as happens in many EU regions). Part or all of the content aggregated and processed by public authorities will also be available in the public domain, both for the benefit of the general public as well as to stimulate the growth of other services. Service and content providers are expected to further classify services based on the cost presented to the end-user. 1) Freely available content and services for individuals (home users, other non-corporate users), accessible by common applications (an advanced “browser” as well as other server-side tools and advanced RWW-search engines) in an augmented web-surfing experience, for everyday, nonprofessional use and without or minimal GoS features. In a regular scenario that is to be encountered more and more in the future, the individual before leaving his/hers home for shopping will be able to request traffic conditions to the nearest commercial area, identify parking availability while he/she requests sales prices. The travelers would even browse across one continent to determine the exact spot for their winter vacations based on snowfall and other criteria. 2) Premium services will be offered by service providers for use by professionals. Such services will be providing certain levels of GoS (these levels defined according to parameters which include accuracy, latency, recency among others) and will be of extreme assistance for professionals gathering required information to support decisions in many domains; for example they will be an invaluable tool for a professional of the agriculture domain on the acquisition of a farm choosing the best according to her needs based on weather information acquired by nearby sensors. B. Revenue Flow and Charging Models The revenue models envisaged may not be directly deduced from existing services however they may be classified according to this experience. 1. Direct Revenues – Direct revenues are expected to be made by the introduction of Premium Services available for endusers as well for other members of the WSN value chain. A synthesis of one or more of the following charging models will be used for charging the services provisioned. a) Flat-rate – User is charged once the same fee, regardless of the number of the services he/she uses or volume of network resources required. b) Volume-based – User is charged based on the volume of information units exchanged (this model especially suits the case of WSN infrastructure owners who may charge for any transaction that depletes the energy of their sensors) c) Subscription – Users subscribe to the service or application and are thus charged periodically (monthly/yearly). Several subscription levels may be foreseen according to the relevant Grade of Service levels expected by the customer. d) Transaction – in this case the user is charged one-off for a specific activity (e.g. the download of a file or an application, or a data stream) 2. Indirect Revenues – Indirect revenues are expected to finance the survival and growth of service offerings other than the Premium ones. The main sources of income in this case refer to income from all types of promotion (advertisers pay a fee for promoting their products, while content aggregators pay fees for being selected as exclusive content providers).
Panayotis Kikiras et al: WIRELESS SENSOR NETWORKS: BUSINESS MODELS AND MARKET ISSUES
Fig. 5. RWW Income Flow
V. CONCLUSIONS The growth and maturity of wireless and ubiquitous networking, together with the abundance of cheap sensors -we already live in a world that contains more sensors than people - brings about the conditions to expand and enrich the way we experience our environment via the internet and the broadcast media. In this contribution, the evolution of the currently non-existent WSN-based services market to the envisaged global-reaching, information-abundant, internetworked universe we refer to as the Real-World Web (RWW), is treated in the conventional way internet and mobile services were treated in recent years. It is however probable that - given the right environment for their growth, the overwhelming quantity, the high quality and high value of the emerging RWW services will prove our conventional views (as well as methodologies and tools) of the current eservices market, insufficient to deal with this and other challenging domains. REFERENCES [1] [2] [3] [4] [5] [6]
Adam Wolisz , ed., (2003), “A short survey of wireless sensor networks”, Technical University Berlin Telecommunication Networks Group (TKN), TKN Technical Report TKN-03-018, 2003. Gartner Research (2005), “Hype Cycle for Wireless Networking, 2005”, Document ID Number: G00127884, 29 June 2005. I.F.Akyildiz et al. (2002), “Wireless Sensor Networks: A Survey”, Computer Networks, Elsevier Journal, March 2002. Jackie Fenn (2005),"The Real-World Web Will Connect Objects and Places", Gartner Research Document ID Number: G00125772, 2005. Karl H, Willig A. (2005), “Protocols and Architectures for WSN”, Wiley 2005. Vassileios Tsetsos, George Alyfantis, Tilemahos Hasiotis, Odysseas Sekkas, and Stathes Hadjiefthymiades (2005), “Commercial Wireless Sensor Networks: Technical and Business Issues”, Wireless On demand Network Systems and Services (WONS) 2005.
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