Clustering algorithms for sensor networks and mobile ad hoc networks to improve energy efficiency

Includes bibliographical references (leaves 161-172).Many clustering algorithms have been proposed to improve energy efficiency of ad hoc networks as this is one primary challenge in ad hoc networks. The design of these clustering algorithms in sensor networks is different from that in mobile ad hoc networks in accordance with their specific characteristics and application purposes. A typical sensor network, which consists of stationary sensor nodes, usually has a data sink because of the limitation on processing capability of sensor nodes. The data traffic of the entire network is directional towards the sink. This directional traffic burdens the nodes/clusters differently according to their distance to the sink. Most clustering algorithms assign a similar number of nodes to each cluster to balance the burden of the clusters without considering the directional data traffic. They thus fail to maximize network lifetime. This dissertation proposes two clustering algorithms. These consider the directional data traffic in order to improve energy efficiency of homogeneous sensor networks with identical sensor nodes and uniform node distribution. One algorithm is for sensor networks with low to medium node density. The other is for sensor networks with high node density. Both algorithms organize the clusters in such a way that the cluster load is proportional to the cluster energy stored, thereby equalizing cluster lifetimes and preventing premature node/cluster death. Furthermore, in a homogeneous sensor network with low to medium node density, the clusterhead is maintained in the central area of the cluster through re-clustering without ripple effect to save more energy. The simulation results show that the proposed algorithms improve both the lifetime of the networks and performance of data being delivered to the sink. A typical mobile ad hoc network, which usually consists of moveable nodes, does not have a data sink. Existing energy-efficient clustering algorithms maintain clusters by periodically broadcasting control messages. In a typical mobile ad hoc network, a greater speed of node usually needs more frequent broadcasting. To efficiently maintain the clusters, the frequency of this periodic broadcasting needs to meet the requirement of the potentially maximum speed of node. When the node speed is low, the unnecessary broadcasting may waste significant energy. Furthermore, some clustering algorithms limit the maximum cluster size to moderate the difference in cluster sizes. Unfortunately, the cluster sizes in these algorithms still experience significant difference. The larger clusters will have higher burdens. Some clustering algorithms restrict the cluster sizes between the maximum and minimum limits. The energy required to maintain these clusters within the maximum and minimum sizes is quite extensive, especially when the nodes are moving quickly. Thus, energy efficiency is not optimized

Unicast Barrage Relay Networks: Outage Analysis and Optimization

Barrage relays networks (BRNs) are ad hoc networks built on a rapid cooperative flooding primitive as opposed to the traditional point-to-point link abstraction. Controlled barrage regions (CBRs) can be used to contain this flooding primitive for unicast and multicast, thereby enabling spatial reuse. In this paper, the behavior of individual CBRs is described as a Markov process that models the potential cooperative relay transmissions. The outage probability for a CBR is found in closed form for a given topology, and the probability takes into account fading and co-channel interference (CCI) between adjacent CBRs. Having adopted this accurate analytical framework, this paper proceeds to optimize a BRN by finding the optimal size of each CBR, the number of relays contained within each CBR, the optimal relay locations when they are constrained to lie on a straight line, and the code rate that maximizes the transport capacity.Comment: 7 pages, 4 figures, 1 table, in IEEE Military Commun. Conf. (MILCOM), 201

Ripple effect : an improved geographic routing with local connectivity information

One of the key challenges in geographic routing is how to deal with dead-ends, where greedy routing fails to find a neighbor node which is closer to the destination. Most existing geographic routing algorithms just switch to the deterministic face routing or limits its face searching range. In this paper, we demonstrate that we can improve routing performance by considering local connectivity status at each node before making routing decision. We present a protocol, Density Ripple Exchange (DRE), that maintains local density information at each node, and a new geographic routing algorithm, Geographic Ripple Routing (GRR), that achieves better routing performance in both hop stretch and transmission stretch than existing geographic routing algorithms by exploiting available connectivity information. Our simulations demonstrate that we increased the performance for GRR over Greedy Perimeter Stateless Routing (GPSR) by about 15%. The cost of this improved performance is a small amount of additional local connectivity information required for our algorithm.<br /

Concurrent Transmissions for Multi-hop Bluetooth 5

Bluetooth is an omnipresent communication technology, available on billions of connected devices today.While it has been traditionally limited to peer-to-peer and star network topology, the recent Bluetooth 5 standard introduces new operating modes to allow for increased reliability and Bluetooth Mesh supports multi-hop networking based on message flooding.In this paper, we present BlueFlood.It adapts concurrent transmissions, as introduced by Glossy, to Bluetooth.The result is fast and efficient network-wide data dissemination in multi-hop Bluetooth networks.Moreover, we show that BlueFlood floods can be reliably received by off-the-shelf Bluetooth devices such as smart phones, opening new applications of concurrent transmissions and seamless integration with existing technologies. We present an in-depth experimental feasibility study of concurrent transmissions over Bluetooth PHY in a controlled environment.Further, we build a small-scale testbed where we evaluate BlueFlood in real-world settings of a residential environment.We show that\ua0BlueFlood achieves 99% end-to-end delivery ratio in multi-hop networks with a duty cycle of 0.13% for 1-second intervals