Design and analysis of a multi-candidate selection scheme for greedy routing in wireless sensor networks

Nguyen, Dang Tu; Choi, Wook; Ha, Minh Thiep; Choo, Hyunseung

doi:10.1016/j.jnca.2010.12.009

Cited by 9 publications

(11 citation statements)

References 25 publications

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“…Probabilistic routing algorithms: In routing protocols of sensor networks, probabilistic routing was proposed for a sender to choose one of its potential receivers to relay the message based on different kinds of routing probability assignment strategies, such as the geographic routing [25,26], receiver contention routing and multi-path probabilistic routing [27,28]. Some studies have revealed the benefits of probabilistic routing.…”

Section: Related Workmentioning

confidence: 99%

Distributed probabilistic routing for sensor network lifetime optimization

Wang

Tan

2015

Wireless Netw

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A probabilistic and distributed routing approach for multi-hop sensor network lifetime optimization is presented in this paper. In particular, each sensor self-adjusts their routing probabilities locally to their forwarders based on its neighborhood knowledge, while aiming at optimizing the overall network lifetime (defined as the elapsed time before the first node runs out of energy). The theoretical feasibility and a practical routing algorithm are presented. Specifically, a sufficient distributed condition regarding the neighborhood state for distributed probabilistic routing to achieve the optimal network lifetime is presented theoretically. Based on it, a distributed adaptive probabilistic routing (DAPR) algorithm, which considered both the transmission scheduling and the routing probability evolvement is developed. We prove quantitatively that DAPR could lead the routing probabilities of the distributed sensors to converge to an optimal state which optimizes the network lifetime. Further, when network dynamics happen, such as topology changes, DAPR can adjust the routing probabilities quickly to converge to a new state for optimizing the remained network lifetime. We presented the convergence speed of DAPR. Extensive simulations verified its convergence and near-optimal properties. The results also showed its quick adaptation to both the network topology and data rate dynamics.

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Section: Related Workmentioning

confidence: 99%

Distributed probabilistic routing for sensor network lifetime optimization

Wang

Tan

2015

Wireless Netw

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“…The proposed scheme extended the traditional uniform grid-based routing scheme by dynamically partition the network to achieve better energy utilization. The authors proposed multi-candidate selection (MCS) and latency-adaptive distance-based multi-candidate (LDMS) schemes together with greedy routing to achieve lower delivery latency under the constraint of sleep and wake-up scheduling of sensor nodes (Nguyen et al, 2011).…”

Section: Related Workmentioning

confidence: 99%

Energy consumption bounds analysis and its applications for grid based wireless sensor networks

Peng

Chen

2013

Journal of Network and Computer Applications

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“…[14][15][16][17]24]. In this section, we focus on routing problem and some related research efforts.…”

Section: Related Workmentioning

confidence: 99%

“…Recently, duty-cycled WSNs have attracted a lot of attention. The research efforts are on data collection [21], data International Journal of Distributed Sensor Networks forwarding [22], load balancing [23], and routing [14][15][16][17]24]. In this section, we focus on routing problem and some related research efforts.…”

Section: Related Workmentioning

confidence: 99%

“…Here, we do not consider the case that the power of sensing device and radio transceiver can be separately controlled because sensors are usually tiny, cheap, and integrated devices. This assumption is also adopted in [1,3,5,16,17].To simplify discussion, we assume that each cycle consists of slots and each node has one working period in each cycle, denoted by [ , ]. Note that this assumption is not mandatory because our routing algorithm is applicable for the case that each node has multiple working periods in a cycle.…”

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confidence: 99%

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Routing in Duty-Cycled Surveillance Sensor Networks

Shen

Zhang

2013

International Journal of Distributed Sensor Networks

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In many surveillance sensor networks, sensors are scheduled to work in a duty-cycled mode (i.e., periodically switching between active states and sleeping states) in order to prolong the network lifetime. The duty-cycled mode saves sensors' energy but brings other issues. In surveillance applications (e.g., forest fire alarm or intruder detection), it is desired to report detected events to the sink node as soon as possible. However, the duty-cycled mode may increase the data delivery latency. In this paper, we study minimum-delay routing in duty-cycled surveillance sensor networks. As the minimum-delay routes are time dependent (i.e., they change with time) in duty-cycled sensor networks, routing becomes a challenging task. We propose a distributed routing algorithm to find the minimum-delay routes at any time from all nodes to the sink node. Further, all minimum-delay routes can be found in one execution of our routing algorithm. We further provide a distributed route maintenance algorithm for finding the minimum-delay routes when the network dynamically changes. We theoretically prove the correctness of the proposed algorithm, and extensive simulation results show that the performance of our algorithm outperforms other existing algorithms. IntroductionWireless sensor networks (WSNs) have been used in many surveillance applications such as traffic monitoring, forest fire detection, and target tracking. Typically, in surveillance system, sensors (or nodes) detect events and then report the events to the base station (or the sink node). To build longterm operating surveillance systems, sensors are expected to work for months or even years, but they only have limited battery energy. For example, the battery of a sensor can only last for a few days if running continuously. One viable technique is to schedule sensors switching between active mode and sleeping mode, while active sensors perform surveillance tasks. Energy-efficient scheduling algorithms [1][2][3][4][5][6][7] are proposed in the literature to prolong network lifetime, as well as to guarantee event detection. In these algorithms, sensors are scheduled to be active for a period of time and then to sleep for another period of time, which forms a duty-cycled WSN.As pointed out by [8], the effectiveness of a surveillance system lies in two aspects: accurately detecting events and timely reporting the events. The second aspect is highly related to routing problem. Routing in WSNs has been extensively studied and many routing algorithms or protocols are proposed. The research on routing evolves from early flooding-based protocols to location-based routing protocols (with the help of localization methods [9,10]) and to stateof-the-art gradient-based routing protocols [11]. Collection tree protocol (CTP) [12] and routing protocol for low-power and lossy networks (RPL) [13] are two well-known gradientbased routing protocols. CTP uses expected transmissions (ETX) as the gradient that indicates the expected number of transmissions needed for the packet to reach t...

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Design and analysis of a multi-candidate selection scheme for greedy routing in wireless sensor networks

Cited by 9 publications

References 25 publications

Distributed probabilistic routing for sensor network lifetime optimization

Distributed probabilistic routing for sensor network lifetime optimization

Energy consumption bounds analysis and its applications for grid based wireless sensor networks

Routing in Duty-Cycled Surveillance Sensor Networks

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