Distributed services for information dissemination in self-organizing sensor networks

Lim, Alvin

doi:10.1016/s0016-0032(01)00020-5

Cited by 49 publications

(15 citation statements)

References 16 publications

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“…A system architecture proposed by Lim in [42], which is specialized in sensor network systems enlightens us on our system design. The whole sensor network infrastructure is divided into three layers:…”

Section: Resource Discoverymentioning

confidence: 99%

“…Bluetooth [41] devices have a range of 10 meter and can directly communicate with at most seven other Bluetooth devices in a piconet. Bluetooth Service Discovery Protocol (SDP) [42] allows devices to browse and retrieve services by matching service classes or device attributes. Only services within the range of the device are returned.…”

Section: Resource Discoverymentioning

confidence: 99%

Section: Resource Discoverymentioning

confidence: 99%

“…Due to distance limitation of Bluetooth, its SDP can only retrieve service with range of 10 meters. The lookup service provided by [42] may retrieves services that could be multiple hops from the requesting node.A system architecture proposed by Lim in [42], which is specialized in sensor network systems enlightens us on our system design. The whole sensor network infrastructure is divided into three layers:…”

mentioning

confidence: 99%

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A Distributed System for Mad-Cow Disease Monitoring and Tracking

Zhang¹

2010

IJU

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Advances in hardware technology and wireless communication have enabled the deployment of largescale sensor networks, where thousands to millions of self-powered, small and low-cost sensor nodes are distributed over a vast field to obtain sensing data. These sensor nodes are equipped with sensing, communicating, and data processing units, which allow sensor nodes to collect, exchange, and process data of the environment. The processing units used in the current generation of sensor nodes are already powerful enough to perform some complicated algorithms to process sensing data, and they are expected to be more powerful in the future. Due to these attractive characteristics, wireless sensor networks are ideal candidates for a wide range of civil applications and military operations. This paper provides an indepth study of applying wireless sensor networks to real-world mad-cow disease monitoring and beef distribution safety system. An extensive survey of the state of the art to design a distributed system for pervasive computing is conducted. A set of techniques and mechanisms are compared and ranked in the paper. Then the characteristics for designing this kind of pervasive system are listed; the system architecture is presented; and an instance of the key mechanisms for monitoring the mad-cow disease and tracking beef distribution system is presented. This system supports real-time communication and multitasking scheduling as well. KEYWORDSSensor Networks, Distributed System, Mad-Cow Disease (MCD) INTRODUCTIONSince Mark Weiser described the vision of pervasive computing in his seminal paper [1], a lot of progress has been achieved in this area. With the advance in MEMS devices and embedded processors and radio, it will soon be feasible to deploy large-scale sensor networks to perform distributed microsensing and control of physical environment [2]. For example, Civil engineers are using motes to monitor building integrity during earthquakes [3]; biologists are planning mote deployments for habitat monitoring [4], [5]; administrators of large computer clusters are using motes to monitor the temperature and power usage in their data centers.Recently, people are considering using sensors to monitor and track the mad-cow disease. The fast spread of mad-cow disease has caused severe results in the past. People got contaminated and economics was also affected by this event. To avoid disease spread out and track the distribution of beef, recording sensors have been put in different processing procedures [6]. The smart sensors and actuators are equipped with low-power processors and short-range radio 2 transceivers. They will automatically form multi-hop ad hoc networks to communicate with other sensors and remote base stations as well.Radio Frequency Identification (RFID) (Figure 1) has been used by PM Beef on cow/calf farms, feedlots and PM's harvest and fabrication facility in Windam, MN [7]. However, those RFIDs act only as identification: They do not group into sensor networks. Figure 1. RFID tagsThis...

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Section: Resource Discoverymentioning

confidence: 99%

Section: Resource Discoverymentioning

confidence: 99%

Section: Resource Discoverymentioning

confidence: 99%

mentioning

confidence: 99%

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A Distributed System for Mad-Cow Disease Monitoring and Tracking

Zhang¹

2010

IJU

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“…In order to support dynamic, self-organizing sensor networks, three fundamental services for sensor networks have been proposed: lookup service, composition service, and adaptation service [18]. These services shield higher level services and applications from the difficulties inherent in the dynamic nature of sensor networks.…”

Section: Distributed Servicesmentioning

confidence: 99%

A Sensor Network Architecture for Tsunami Detection and Response

Casey

Lim

Dozier

2008

International Journal of Distributed Sensor Networks

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Channel allocation and reallocation for cognitive radio networks

Jiang¹,

Wang²,

Leng³

2011

Wireless Communications

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In this paper, a new channel allocation and re-location scheme is proposed for cognitive radio users to efficiently utilize available spectrums. We also present a multiple-dimension Markov analytical chain to evaluate the performance of this scheme. Both analytical results and simulation results demonstrate that the new scheme can enhance the radio system performance significantly in terms of blocking probability, dropping probability, and throughput of second users. The proposed scheme can work as a non-server-based channel allocation, which has practical values in real engineering design. Copyright

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Distributed services for information dissemination in self-organizing sensor networks

Cited by 49 publications

References 16 publications

A Distributed System for Mad-Cow Disease Monitoring and Tracking

A Distributed System for Mad-Cow Disease Monitoring and Tracking

A Sensor Network Architecture for Tsunami Detection and Response

Channel allocation and reallocation for cognitive radio networks

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