639 research outputs found

    Smaller Connected Dominating Sets in Ad Hoc and Sensor Networks based on Coverage by Two-Hop Neighbors

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    In this paper, we focus on the construction of an efficient dominating set in ad hoc and sensor networks. A set of nodes is said to be dominating if each node is either itself dominant or neighbor of a dominant node. This set can for example be used for broadcasting, so the smaller the set is, the more efficient it is. As a basis for our work, we use a heuristics given by Dai and Wu for constructing such a set and propose an enhanced definition to obtain smaller sets. This approach, in conjunction with the elimination of message overhead by Stojmenovic, has been shown (in recent studies) to be an excellent compromise with respect to a wide range of metrics considered. In our new definition, a node u is not dominant if there exists in its 2-hop neighborhood a connected set of nodes with higher priorities that covers u and its 1-hop neighbors. This new rule uses the exact same level of information required by the original heuristics, only neighbors of nodes and neighbors of neighbors must be known to apply it, but it takes advantage of some knowledge originally not taken into account: 1-hop neighbors can be covered by some 2-hop neighbors. We give the proof that the set obtained with this new definition is a subset of the one obtained with Dai and Wu's heuristics. We also give the proof that our set is always dominating for any graph, and connected for any connected graph. Two versions were considered: with topological and positional information, which differ in whether or not nodes are aware of links between their 2-hop neighbors that are not 1-hop neighbors. An algorithm for applying the concept at each node is described. We finally provide experimental data that demonstrates the superiority of our rule in obtaining smaller dominating sets. A centralized algorithm was used as a benchmark in the comparison. The overhead of the size of connected dominating set was reduced by about 15% with the topological variant and by about 30% with the positional variant of our new definition

    Smaller Connected Dominating Sets in Ad Hoc and Sensor Networks based on Coverage by Two-Hop Neighbors

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    International audienceIn this paper, we focus on the construction of an efficient dominating set in ad hoc and sensor networks. A set of nodes is said to be dominating if each node is either itself dominant or neighbor of a dominant node. Application of such a set may for example be broadcasting, where the size of the set greatly impacts on energy consumption. Obtaining small sets is thus of prime importance. As a basis for our work, we use a heuristic given by Dai and Wu for constructing such a set. Their approach, in conjunction with the elimination of message overhead by Stojmenovic, has been recently shown to be an excellent compromise with respect to a wide range of metrics. In this paper, we present an enhanced definition to obtain smaller sets in the specific case where 2-hop information is considered. In our new definition, a node u is not dominant if there exists in its 2-hop neighborhood a connected set of nodes with higher priorities that covers u and its 1-hop neighbors. This new rule requires the same level of knowledge used by the original heuristic: only neighbors of nodes and neighbors of neighbors must be known to apply it. However, it takes advantage of some topological knowledge originally not taken into account, that may be used to deduce communication links between 1-hop and 2-hop neighbors. We provide the proof that the new set is a subset of the one obtained with the original heuristic. We also give the proof that our set is always dominating for any graph, and connected for any connected graph. Two versions are considered: with topological and positional information, which differ in whether or not nodes are aware of links between their 2-hop neighbors that are not 1-hop neighbors. An algorithm for locally applying the concept at each node is described. We finally provide experimental data that demonstrates the superiority of our rule in obtaining smaller dominating sets. A centralized algorithm is used as a benchmark in the comparisons. The overhead of the size of connected dominating set is reduced by about 15% with the topological variant and by about 30% with the positional variant of our new definition

    Maximizing the Probability of Delivery of Multipoint Relay Broadcast Protocol in Wireless Ad Hoc Networks with a Realistic Physical Layer

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    It is now commonly accepted that the unit disk graph used to model the physical layer in wireless networks does not reflect real radio transmissions, and that the lognormal shadowing model better suits to experimental simulations. Previous work on realistic scenarios focused on unicast, while broadcast requirements are fundamentally different and cannot be derived from unicast case. Therefore, broadcast protocols must be adapted in order to still be efficient under realistic assumptions. In this paper, we study the well-known multipoint relay protocol (MPR). In the latter, each node has to choose a set of neighbors to act as relays in order to cover the whole 2-hop neighborhood. We give experimental results showing that the original method provided to select the set of relays does not give good results with the realistic model. We also provide three new heuristics in replacement and their performances which demonstrate that they better suit to the considered model. The first one maximizes the probability of correct reception between the node and the considered relays multiplied by their coverage in the 2-hop neighborhood. The second one replaces the coverage by the average of the probabilities of correct reception between the considered neighbor and the 2-hop neighbors it covers. Finally, the third heuristic keeps the same concept as the second one, but tries to maximize the coverage level of the 2-hop neighborhood: 2-hop neighbors are still being considered as uncovered while their coverage level is not higher than a given coverage threshold, many neighbors may thus be selected to cover the same 2-hop neighbors

    Energy efficient clustering and secure data aggregation in wireless sensor networks

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    Communication consumes the majority of a wireless sensor network\u27s limited energy. There are several ways to reduce the communication cost. Two approaches used in this work are clustering and in-network aggregation. The choice of a cluster head within each cluster is important because cluster heads use additional energy for their responsibilities and that burden needs to be carefully distributed. We introduce the energy constrained minimum dominating set (ECDS) to model the problem of optimally choosing cluster heads in the presence of energy constraints. We show its applicability to sensor networks and give an approximation algorithm of O(log n) for solving the ECDS problem. We propose a distributed algorithm for the constrained dominating set which runs in O(log n log [triangle]) rounds with high probability. We show experimentally that the distributed algorithm performs well in terms of energy usage, node lifetime, and clustering time and thus is very suitable for wireless sensor networks. Using aggregation in wireless sensor networks is another way to reduce the overall communication cost. However, changes in security are necessary when in- network aggregation is applied. Traditional end-to-end security is not suitable for use with in-network aggregation. A corrupted sensor has access to the intermediate data and can falsify results. Additively homomorphic encryption allows for aggregation of encrypted values, with the result being the same as the result as if unencrypted data were aggregated. Using public key cryptography, digital signatures can be used to achieve integrity. We propose a new algorithm using homomorphic encryption and additive digital signatures to achieve confidentiality, integrity and availability for in- network aggregation in wireless sensor networks. We prove that our digital signature algorithm which is based on Elliptic Curve Digital Signature Algorithm (ECDSA) is at least as secure as ECDSA. Even without in-network aggregation, security is a challenge in wireless sensor networks. In wireless sensor networks, not all messages need to be secured with the same level of encryption. We propose a new algorithm which provides adequate levels of security while providing much higher availablility [sic] than other security protocols. Our approach uses similar amounts of energy as a network without security --Abstract, page iv

    An analysis of the lifetime of OLSR networks

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    The Optimized Link State Routing (OLSR) protocol is a well-known route discovery protocol for ad-hoc networks. OLSR optimizes the flooding of link state information through the network using multipoint relays (MPRs). Only nodes selected as MPRs are responsible for forwarding control traffic. Many research papers aim to optimize the selection of MPRs with a specific purpose in mind: e.g., to minimize their number, to keep paths with high Quality of Service or to maximize the network lifetime (the time until the first node runs out of energy). In such analyzes often the effects of the network structure on the MPR selection are not taken into account. In this paper we show that the structure of the network can have a large impact on the MPR selection. In highly regular structures (such as grids) there is even no variation in the MPR sets that result from various MPR selection mechanisms. Furthermore, we study the influence of the network structure on the network lifetime problem in a setting where at regular intervals messages are broadcasted using MPRs. We introduce the ’maximum forcedness ratio’, as a key parameter of the network to describe how much variation there is in the lifetime results of various MPR selection heuristics. Although we focus our attention to OLSR, being a widely implemented protocol, on a more abstract level our results describe the structure of connected sets dominating the 2-hop neighborhood of a node

    On Clustering in Sensor Networks

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    Self-* distributed query region covering in sensor networks

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    Wireless distributed sensor networks are used to monitor a multitude of environments for both civil and military applications. Sensors may be deployed to unreachable or inhospitable areas. Thus, they cannot be replaced easily. However, due to various factors, sensors\u27 internal memory, or the sensors themselves, can become corrupted. Hence, there is a need for more robust sensor networks. Sensors are most commonly densely deployed, but keeping all sensors continually active is not energy efficient. Our aim is to select the minimum number of sensors which can entirely cover a particular monitored area, while remaining strongly connected. This concept is called a Minimum Connected Cover of a query region in a sensor network. In this research, we have designed two fully distributed, robust, self-* solutions to the minimum connected cover of query regions that can cope with both transient faults and sensor crashes. We considered the most general case in which every sensor has a different sensing and communication radius. We have also designed extended versions of the algorithms that use multi-hop information to obtain better results utilizing small atomicity (i.e., each sensor reads only one of its neighbors\u27 variables at a time, instead of reading all neighbors\u27 variables). With this, we have proven self-* (self-configuration, self-stabilization, and self-healing) properties of our solutions, both analytically and experimentally. The simulation results show that our solutions provide better performance in terms of coverage than pre-existing self-stabilizing algorithms

    A backbone-based communication scheduling scheme for wireless sensor networks

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    Prolonging network lifetime and retaining maximum communication fidelity are important to many applications of ad-hoc wireless sensor networks. Many energy-efficient communication protocols have been proposed to allow as many sensors as possible to be in idling. Typically, these techniques reduce energy consumption by minimizing the number of transmission packets and the size of each packet. However, recent researches have shown that energy consumed by the sensors in idling state is not negligible. In this research, we address this problem with a novel Backbone-based Communication Scheduling (BCS) technique. This scheme reduces the idling energy dissipation by keeping only a small set of sensors active at any time and leaving the rest of them in sleeping. The active sensors form a communication backbone that maintains the communication fidelity of the entire network. The backbone nodes are rotated with a highly efficient backbone election algorithm to balance the energy consumption of the sensors in the whole network. Our simulations results show that the proposed scheme can significantly extend the network lifetime without compromising the communication fidelity

    A survey on energy efficient techniques in wireless sensor networks

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    International audienceThe myriad of potential applications supported by wireless sensor networks (WSNs) has generated much interest from the research community. Various applications range from small size low industrial monitoring to large scale energy constrained environmental monitoring. In all cases, an operational network is required to fulfill the application missions. In addition, energy consumption of nodes is a great challenge in order to maximize network lifetime. Unlike other networks, it can be hazardous, very expensive or even impossible to charge or replace exhausted batteries due to the hostile nature of environment. Researchers are invited to design energy efficient protocols while achieving the desired network operations. This paper focuses on different techniques to reduce the consumption of the limited energy budget of sensor nodes. After having identified the reasons of energy waste in WSNs, we classify energy efficient techniques into five classes, namely data reduction, control reduction, energy efficient routing, duty cycling and topology control. We then detail each of them, presenting subdivisions and giving many examples. We conclude by a recapitulative table
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