Market mechanisms for resource allocation in pervasive sensor applications

Geyik, Sahin Cem; Shah, Syed Yousaf; Szymanski, Boleslaw K.; Das, Sanmay; Zerfos, Petros

doi:10.1016/j.pmcj.2012.03.004

Cited by 5 publications

(4 citation statements)

References 17 publications

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“…We note here that while Wei et al [2010] presented a theoretical performance analysis of target tracking with a Brownian-motion-modeled moving target, Chen et al [2008] studied market-based techniques to manage the operation of a sensor network tracking a target moving in a deterministicallyconstrained manner with the objective to minimize information value loss. We further note that in subsequent maturations of the latter work, such as Geyik et al [2012], the authors progressed from an originally loose distinction between quality and value of information to a more concrete separation of QoI and VoI along the lines of Bisdikian et al [2009b], where QoI reflected the effectiveness of a sensor network in providing information, for example, the latency experienced in delivering information, and VoI was derived from the QoI and the application context. This separation provided [Geyik et al 2012] a more solid framework for executing their management operations and applying the market-based techniques to additional use scenarios as well.…”

Section: Summary and Concluding Remarksmentioning

confidence: 93%

On the quality and value of information in sensor networks

Bisdikian

Kaplan

Srivastava

2013

ACM Trans. Sen. Netw.

116

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The increasing use of sensor-derived information from planned, ad-hoc, and/or opportunistically deployed sensor networks provides enhanced visibility to everyday activities and processes, enabling fast-paced datato-decision in personal, social, civilian, military, and business contexts. The value that information brings to this visibility and ensuing decisions depends on the quality characteristics of the information gathered. In this article, we highlight, refine, and extend upon our past work in the areas of quality and value of information (QoI and VoI) for sensor networks. Specifically, we present and elaborate on our two-layer QoI/VoI definition, where the former relates to context-independent aspects and the latter to context-dependent aspects of an information product. Then, we refine our taxonomy of pertinent QoI and VoI attributes anchored around a simple ontological relationship between the two. Finally, we introduce a framework for scoring and ranking information products based on their VoI attributes using the analytic hierarchy multicriteria decision process, illustrated via a simple example. ACM Reference Format:Bisdikian, C., Kaplan, L. M., and Srivastava, M. B. 2013. On the quality of information in sensor networks.

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Section: Summary and Concluding Remarksmentioning

confidence: 93%

On the quality and value of information in sensor networks

Bisdikian

Kaplan

Srivastava

2013

ACM Trans. Sen. Netw.

116

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“…Some recent studies in the literature, such as [73], do not differentiate between VoI and Quality of Information (QoI), which is defined by Sachidananda et al [6] as "the user's perceived quality towards the information." However, Geyik et al [74] distinguish between VoI and QoI, and Bisdikian et al [56] introduce a taxonomy for both QoI and VoI attributes. Both consider QoI as an objective measure of the information utility which can be determined from the information object only.…”

Section: A Quality Attributes Of Informationmentioning

confidence: 99%

Value of Information in Wireless Sensor Network Applications and the IoT: A Review

Alawad

Kraemer

2022

IEEE Sensors J.

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Value of Information (VoI) is a concept to assess the usefulness of information for a specific goal, and has in the last decade experienced a growing interest also for Wireless Sensor Network (WSN) applications and the Internet of Things (IoT). By making the value of information explicit in the form of VoI, WSN and IoT applications should be able to better assess which information to spend their constrained resources on. However, the definition of VoI is highly application-dependent, which has led to a fragmented understanding of VoI, and there is a lack of a comprehensive overview. In this structured review, we first categorize application use cases and examine what VoI is used for, and explore the different approaches to defining VoI. We then provide a well-structured and comprehensive discussion of the specific approaches used in the literature to determine VoI, together with examples of use cases. We categorize the different approaches to calculating VoI, describe their properties systematically and distinguish between observed VoI and expected VoI. We also discuss adaptive VoI approaches and point towards future directions within the field.

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“…For example, if the packet has not passed the congested node yet, the node does not approximate the time delay, meaning that the loss of information utility cannot be evaluated exactly. To allow the congested node to make more efficient decisions, the authors in [153] introduced a traveling auction scheme in which a node can share its local auction information with its neighbors. The traveling auction is similar to the auction scheme in [150] with the addition of the information sharing mechanism among nodes in the network.…”

Section: Congestion Managementmentioning

confidence: 99%

Data Collection and Wireless Communication in Internet of Things (IoT) Using Economic Analysis and Pricing Models: A Survey

Luong

Hoang

Wang

et al. 2016

IEEE Commun. Surv. Tutorials

292

124

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Abstract-This paper provides a state-of-the-art literature review on economic analysis and pricing models for data collection and wireless communication in Internet of Things (IoT). Wireless Sensor Networks (WSNs) are the main component of IoT which collect data from the environment and transmit the data to the sink nodes. For long service time and low maintenance cost, WSNs require adaptive and robust designs to address many issues, e.g., data collection, topology formation, packet forwarding, resource and power optimization, coverage optimization, efficient task allocation, and security. For these issues, sensors have to make optimal decisions from current capabilities and available strategies to achieve desirable goals. This paper reviews numerous applications of the economic and pricing models, known as intelligent rational decision-making methods, to develop adaptive algorithms and protocols for WSNs. Besides, we survey a variety of pricing strategies in providing incentives for phone users in crowdsensing applications to contribute their sensing data. Furthermore, we consider the use of some pricing models in Machine-to-Machine (M2M) communication. Finally, we highlight some important open research issues as well as future research directions of applying economic and pricing models to IoT.

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Market mechanisms for resource allocation in pervasive sensor applications

Cited by 5 publications

References 17 publications

On the quality and value of information in sensor networks

On the quality and value of information in sensor networks

Value of Information in Wireless Sensor Network Applications and the IoT: A Review

Data Collection and Wireless Communication in Internet of Things (IoT) Using Economic Analysis and Pricing Models: A Survey

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