Dynamic Service Execution in Sensor Networks

Chen, Lei; Wang, Zijian; Szymanski, Boleslaw K.; Branch, Joel W.; Verma, Dinesh; Damarla, Raju; Ibbotson, John

doi:10.1093/comjnl/bxp051

Cited by 11 publications

(15 citation statements)

References 18 publications

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“…A distributed auction based mechanism to resolve congestion in distributed manner is proposed in [8]. In this approach every candidate packet bids its predicted utility loss which it will incur, if it is delayed for a transmission slot.…”

Section: Related Workmentioning

confidence: 99%

“…Every time unit, the router transmits one packet. We incorporate auction mechanism described in [8] for selecting winner of the transmission slot. Assuming TDMA as medium sharing protocol, application i bids its QoI loss represented by the following utility function.…”

Section: Dynamic Path Selection With Predicted Quality Of Informationmentioning

confidence: 99%

“…Figure 5 shows the decrease of the QoI losses for applications under our PBR protocol as compared to DSDV. In the 2 Priorities: {(5,10), (9,36), (8,64), (16,64), (27,216), (4,16), (10,20)},{(5,10,15), (9,36,81), (8,64,216), (16,64,144), (27,216,729), (4,16,36), (10,20,30)},{ (5,10,15,20), (9,36,81,144), (8,64,216,512), (16,64,144,256), (27,216,729,1728), (4,16,36,64), (10,20,30,40 inte...…”

Section: A Fully Functional Networkmentioning

confidence: 99%

“…Please note that even with DSDV, we use auction mechanism for slot winner selection. In case of DSDV runs shown in all the experiments, when winner of transmission slot is selected using auction mechanism [8], the packet is routed using DSDV protocol as opposed to our proposed routing mechanism. Figure 3 shows decrease in average packet delivery delay.…”

Section: A Fully Functional Networkmentioning

confidence: 99%

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Price based routing for event driven prioritized traffic in wireless sensor networks

Shah

Szymanski

2013

2013 IEEE 2nd Network Science Workshop (NSW)

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Abstract-We present a dynamic price based routing protocol in which packets from different applications dynamically choose their paths by evaluating the price to be paid for taking each path and their ability to pay. We propose a mechanism in which the prices reflect congestion on routers and thus the waiting time for packet to pass through the router. These prices increase as usage of the usually preferred shorter routes increases. The packet's ability to pay price on a router is defined by the product of application's priority and the delay experienced at the router. As a result, the low priority applications intelligently avoid paths with high prices and go via low price routes. The low price routes may possibly be longer but require shorter waiting for passage at congested routers making them faster for low priority packets. This enables high priority traffic to get through quickly via shorter paths as they are able to pay high prices after little wait. Thus, our approach distributes traffic flows of different applications in the network and lowers congestion and delays for all applications. We further show that our dynamic path allocation technique ensures robust communication in fully functional as well as partially damaged networks. Our dynamic pricing mechanism quickly adapts routing to the damaged network, increases utilization of the partial network to lower the impact on critical infrastructure and key resources. Moreover, our proposed mechanism is equally applicable to both communication networks and physical infrastructure networks.

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Section: Related Workmentioning

confidence: 99%

Section: Dynamic Path Selection With Predicted Quality Of Informationmentioning

confidence: 99%

Section: A Fully Functional Networkmentioning

confidence: 99%

Section: A Fully Functional Networkmentioning

confidence: 99%

See 2 more Smart Citations

Price based routing for event driven prioritized traffic in wireless sensor networks

Shah

Szymanski

2013

2013 IEEE 2nd Network Science Workshop (NSW)

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“…Following Chen et al [1], we consider public safety and emergency response needs of a VIP visiting a large city. The streets are equipped with a sophisticated WSN composed of acoustic sensors, closed circuit cameras, chemical fume sensors and so on.…”

Section: An Auction Mechanism For Distributed Congestion Controlmentioning

confidence: 99%

Market mechanisms for Value of Information driven resource allocation in Sensor Networks

Szymanski

Shah

Geyik

et al. 2011

2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops)

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Abstract-This paper examines the possible uses of different market mechanisms for resource allocation at different levels of Wireless Sensor Network (WSN) architecture. The goal is to maximize the Value of Information (VoI) for WSN users. We discuss three different levels of WSN architecture. The lowest level focuses on individual nodes and their basic functions of sensing and routing. We give an example showing how the use of auctions at individual nodes can help to efficiently perform these functions. The middle level focuses on services that are abstractions of applications running on sensors. Complex applications are composed automatically from basic ones. We discuss the use of switch options to address some of the challenges arising in such dynamic service composition. Finally, we consider the highest level -network deployment and sharing -and conjecture that options may be valuable in creating proper incentives for rational deployment and sharing of WSNs.

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In-network outlier detection in wireless sensor networks

et al. 2012

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To address the problem of unsupervised outlier detection in wireless sensor networks, we develop an approach that (1) is flexible with respect to the outlier definition, (2) computes the result in-network to reduce both bandwidth and energy usage, (3) only uses single hop communication thus permitting very simple node failure detection and message reliability assurance mechanisms (e.g., carrier-sense), and (4) seamlessly accommodates dynamic updates to data. We examine performance using simulation with real sensor data streams. Our results demonstrate that our approach is accurate and imposes a reasonable communication load and level of power consumption.Keywords Outlier detection · Wireless sensor networks 1 IntroductionOutlier detection, an essential step preceding most any data analysis routine, is used either to suppress or amplify outliers. The first usage (also known as data cleansing) improves robustness of data analysis. The second usage helps in searching for rare

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Dynamic Service Execution in Sensor Networks

Cited by 11 publications

References 18 publications

Price based routing for event driven prioritized traffic in wireless sensor networks

Price based routing for event driven prioritized traffic in wireless sensor networks

Market mechanisms for Value of Information driven resource allocation in Sensor Networks

In-network outlier detection in wireless sensor networks

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