Mobility-based clustering protocol for wireless sensor networks with mobile nodes
05 Apr 2011-Vol. 1, Iss: 1, pp 39-47
TL;DR: The proposed mobility-based clustering (MBC) protocol outperforms both the CBR protocol and the LEACH-mobile protocol in terms of average energy consumption and average control overhead, and can better adapt to a highly mobile environment.
Abstract: In this study, the authors propose a mobility-based clustering (MBC) protocol for wireless sensor networks with mobile nodes. In the proposed clustering protocol, a sensor node elects itself as a cluster-head based on its residual energy and mobility. A non-cluster-head node aims at its link stability with a cluster head during clustering according to the estimated connection time. Each non-cluster-head node is allocated a timeslot for data transmission in ascending order in a time division multiple address (TDMA) schedule based on the estimated connection time. In the steady-state phase, a sensor node transmits its sensed data in its timeslot and broadcasts a joint request message to join in a new cluster and avoid more packet loss when it has lost or is going to lose its connection with its cluster head. Simulation results show that the MBC protocol can reduce the packet loss by 25% compared with the cluster-based routing (CBR) protocol and 50% compared with the low-energy adaptive clustering hierarchy-mobile (LEACH-mobile) protocol. Moreover, it outperforms both the CBR protocol and the LEACH-mobile protocol in terms of average energy consumption and average control overhead, and can better adapt to a highly mobile environment.
Citations
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TL;DR: A state-of-the-art and comprehensive survey on clustering approaches in WSNs, which surveys the proposed approaches in the past few years in a classified manner and compares them based on different metrics such as mobility, cluster count, cluster size, and algorithm complexity.
433 citations
Cites background from "Mobility-based clustering protocol ..."
...MBC (Deng et al., 2011) Equal Variable 1-hop k-hop Mobile Homogeneous Relay/...
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...Recent compound algorithms: In another work (Deng et al., 2011), a mobility based clustering (MBC) is proposed, of which the main factors of CH election are the residual energy and mobility of the nodes....
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...By extensive simulations, the authors show that MBC outperforms LEACH protocol in terms of better energy consumption and also handles the mobility of the nodes....
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...FLOC (Demirbas et al., 2006) supports the mobility of the regular nodes and (Deng et al., 2011) selects the CHs regarding the mobility of the nodes....
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..., 2006) supports the mobility of the regular nodes and (Deng et al., 2011) selects the CHs regarding the mobility of the nodes....
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TL;DR: This paper provides the taxonomy of various clustering and routing techniques in WSNs based upon metrics such as power management, energy management, network lifetime, optimal cluster head selection, multihop data transmission etc.
430 citations
Cites background from "Mobility-based clustering protocol ..."
...Authors claim that for the highly mobile situation the MBC protocol can reduce the packet loss by 25% as compared with the CBR protocol and 50% as compared with LEACH-mobile protocol....
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...In the proposed scheme, threshold of MBC is changed which includes residual energy and mobility factor....
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...In MBC protocol, selection criterion of CH is different from the classical LEACH protocol; here CH is selected based upon the residual energy and mobility....
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...SEP, BCDCP, BCEE, LEACH-TM, SHRP,LEACH-ER, LEACH-D, and MBC are the most prominent protocols in this category....
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...Key parameters of MBC were packet delivery rate, stable link connection, energy efficiency and lifetime of the network....
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TL;DR: A survey on clustering over the last two decades reveals that QoS aware clustering demands more attention and indicates that clustering techniques enhanced with smart network selection solutions could highly benefit the QoS and QoE in IoT.
Abstract: Wireless sensor network (WSN) systems are typically composed of thousands of sensors that are powered by limited energy resources. To extend the networks longevity, clustering techniques have been introduced to enhance energy efficiency. This paper presents a survey on clustering over the last two decades. Existing protocols are analyzed from a quality of service (QoS) perspective including three common objectives, those of energy efficiency, reliable communication and latency awareness. This review reveals that QoS aware clustering demands more attention. Furthermore, there is a need to clarify how to improve quality of user experience (QoE) through clustering. Understanding the users’ requirements is critical in intelligent systems for the purpose of enabling the ability of supporting diverse scenarios. User awareness or user oriented design is one remaining challenging problem in clustering. In additional, this paper discusses the potential challenges of implementing clustering schemes to Internet of Things (IoT) systems in 5G networks. We indicate that clustering techniques enhanced with smart network selection solutions could highly benefit the QoS and QoE in IoT. As the current studies for WSNs are conducted either in homogeneous or low level heterogeneous networks, they are not ideal or even not able to function in highly dynamic IoT systems with a large range of user scenarios. Moreover, when 5G is finally realized, the problem will become more complex than that in traditional simplified WSNs. Several challenges related to applying clustering techniques to IoT in 5G environment are presented and discussed.
248 citations
03 Nov 2012
TL;DR: This work implemented both centralized and distributed k-means clustering algorithm in network simulator and results show that distributed clustering is efficient than centralized clustering.
Abstract: —A wireless sensor network (WSN) consists of spatially distributed autonomous sensors to monitor physical or environmental conditions and to cooperatively pass their data through the network to a Base Station. Clustering is a critical task in Wireless Sensor Networks for energy efficiency and network stability. Clustering through Central Processing Unit in wireless sensor networks is well known and in use for a long time. Presently clustering through distributed methods is being developed for dealing with the issues like network lifetime and energy. In our work, we implemented both centralized and distributed k-means clustering algorithm in network simulator. k-means is a prototype based algorithm that alternates between two major steps, assigning observations to clusters and computing cluster centers until a stopping criterion is satised. Simulation results are obtained and compared which show that distributed clustering is efficient than centralized clustering. Keywords- wireless sensor network; clustering; ns-2; k-means; network stability
158 citations
TL;DR: About 215 most important WSN clustering techniques are extracted, reviewed, categorized and classified based on clustering objectives and also the network properties such as mobility and heterogeneity, providing highly useful insights to the design of clustering Techniques in WSNs.
150 citations
References
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TL;DR: This work develops and analyzes low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality.
Abstract: Networking together hundreds or thousands of cheap microsensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. These networks require robust wireless communication protocols that are energy efficient and provide low latency. We develop and analyze low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality. LEACH includes a new, distributed cluster formation technique that enables self-organization of large numbers of nodes, algorithms for adapting clusters and rotating cluster head positions to evenly distribute the energy load among all the nodes, and techniques to enable distributed signal processing to save communication resources. Our results show that LEACH can improve system lifetime by an order of magnitude compared with general-purpose multihop approaches.
10,296 citations
TL;DR: Simulation results show that MMSPEED provides QoS differentiation in both reliability and timeliness domains and, as a result, significantly improves the effective capacity of a sensor network in terms of number of flows that meet both reliabilityand timelier requirements up to 50 percent.
Abstract: In this paper, we present a novel packet delivery mechanism called Multi-Path and Multi-SPEED Routing Protocol (MMSPEED) for probabilistic QoS guarantee in wireless sensor networks. The QoS provisioning is performed in two quality domains, namely, timeliness and reliability. Multiple QoS levels are provided in the timeliness domain by guaranteeing multiple packet delivery speed options. In the reliability domain, various reliability requirements are supported by probabilistic multipath forwarding. These mechanisms for QoS provisioning are realized in a localized way without global network information by employing localized geographic packet forwarding augmented with dynamic compensation, which compensates for local decision inaccuracies as a packet travels towards its destination. This way, MMSPEED can guarantee end-to-end requirements in a localized way, which is desirable for scalability and adaptability to large scale dynamic sensor networks. Simulation results show that MMSPEED provides QoS differentiation in both reliability and timeliness domains and, as a result, significantly improves the effective capacity of a sensor network in terms of number of flows that meet both reliability and timeliness requirements up to 50 percent (12 flows versus 18 flows).
863 citations
19 Sep 2003
TL;DR: It is shown that the communication complexity and accuracy of multi-hop synchronization is a function of the construction and depth of the spanning tree; several spanning-tree construction algorithms are described.
Abstract: This paper presents lightweight tree-based synchronization (LTS) methods for sensor networks. First, a single-hop, pair-wise synchronization scheme is analyzed. This scheme requires the exchange of only three messages and has Gaussian error properties. The single-hop approach is extended to a centralized multi-hop synchronization method. Multi-hop synchronization consists of pair-wise synchronizations performed along the edges of a spanning tree. Multi-hop synchronization requires only n-1 pair-wise synchronizations for a network of n nodes. In addition, we show that the communication complexity and accuracy of multi-hop synchronization is a function of the construction and depth of the spanning tree; several spanning-tree construction algorithms are described. Further, the required refresh rate of multi-hop synchronization is shown as a function of clock drift and the accuracy of single-hop synchronization. Finally, a distributed multi-hop synchronization is presented where nodes keep track of their own clock drift and their synchronization accuracy. In this scheme, nodes initialize their own resynchronization as needed.
510 citations
TL;DR: This survey focuses on the video encoding at the video sensors and the real-time transport of the encoded video to a base station, and considers the mechanisms operating at the application, transport, network, and MAC layers.
Abstract: A wireless sensor network with multimedia capabilities typically consists of data sensor nodes, which sense, for instance, sound or motion, and video sensor nodes, which capture video of events of interest. In this survey, we focus on the video encoding at the video sensors and the real-time transport of the encoded video to a base station. Real-time video streams have stringent requirements for end-to-end delay and loss during network transport. In this survey, we categorize the requirements of multimedia traffic at each layer of the network protocol stack and further classify the mechanisms that have been proposed for multimedia streaming in wireless sensor networks at each layer of the stack. Specifically, we consider the mechanisms operating at the application, transport, network, and MAC layers. We also review existing cross-layer approaches and propose a few possible cross-layer solutions to optimize the performance of a given wireless sensor network for multimedia streaming applications.
407 citations
TL;DR: In this article existing proposals that use mobility in WSNs are summarized and a new approach to compute mobile platform trajectories is introduced.
Abstract: Wireless sensor networks are proposed to deliver in situ observations at low cost over long periods of time. Among numerous challenges faced while designing WSNs and protocols, maintaining connectivity and maximizing the network lifetime stand out as critical considerations. Mobile platforms equipped with communication devices can be leveraged to overcome these two problems. In this article existing proposals that use mobility in WSNs are summarized. Furthermore, a new approach to compute mobile platform trajectories is introduced. These solutions are also compared considering various metrics and design goals.
323 citations