An Adaptive Localized Scheme for Energy-Efficient Broadcasting in Ad Hoc Networks with Directional Antennas [chapter]

Julien Cartigny, David Simplot-Ryl, Ivan Stojmenović
<span title="">2004</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
Several solutions for energy-efficient broadcasting, mostly centralized, have been proposed with directional antennas. However, such globalized protocols are not suitable for ad hoc networks, because each node needs a full knowledge of the topology. Recently, a localized algorithm, called DRBOP, using one-to-one communication model has been proposed. It uses RNG graphs, which can be locally computed by each node. However, for energy consumption reasons, it can be useful to reach more than one
more &raquo; ... ighbor at a time. In this paper, we propose an efficient protocol which uses both one-to-one and one-to-many communication models. First, we present a variant of DRBOP efficient for sparse networks, based on LMST graph which is a local adaptation of minimal spanning tree. Then, a one-to-many protocol efficient for dense networks is proposed. From these two algorithms we derive an adaptive protocol which is shown to be efficient for both sparse and dense networks. node can target a subset of its neighborhood with one transmission by choosing direction and width of the beam, using directional antennas. The one-to-one model is a particular case of the previous one, where nodes use a constant narrow beam to transmit toward a particular neighboring node. Since the communication area is a narrow beam with a small angle, the directional antennas provide more energy saving and interference reduction. Several solutions have been proposed [2], [3] for energy-efficient broadcasting with directional antennas. However, they are globalized, meaning either a centralized entity has to gather knowledge of the full topology and diffuse information to organize the network, or each node has to know the total topology of the network to locally compute the broadcast spanning tree. This approach is not efficient in ad hoc networks, because of a high communication overhead. We are interested in localized protocols, which require only information about the neighborhood. Furthermore, we are looking to use directional antennas for the one-to-one and one-to-many models. The problem of finding a broadcast spanning tree with minimal power, and the problem of broadcasting a message with a minimal number of retransmissions are well-known to be both NP-complete [4]. Consequently, several heuristics have been proposed. For instance, MST (Minimum Spanning Tree) [1] is a globalized algorithm which builds the spanning tree by choosing shortest links between nodes. The BIP (Broadcast Incremental Power) algorithm [1] (and the directional version DBIP [3]), proposed by Wieselthier et al. is a globalized greedy algorithm inspired by Prim's algorithm, known to be the most efficient existing broadcast protocol. Some localized solutions also exist. For instance, RBOP (RNG Broadcast Oriented Protocol) [5] (and the directional version DRBOP [6]) is a localized energy-efficient broadcast protocol, which only requires local information to construct a RNG subgraph (Relative Neighborhood Graph) [7] while keeping the network connected. Another recent solution is BLMST, (Broadcast with Local Minimum Spanning Tree) [8] (and a similar independently proposed solution in [9]) is a localized energy-efficient broadcast algorithm for omnidirectional antennas. It is based on LMST (Local Minimum Spanning Tree) [10], a MST algorithm applied on the local neighborhood. In this paper, we propose DLBOP (Directed LMST Broadcast Oriented Protocol), an algorithm based on LMST and using directional antennas. This protocol is a straightforward variation of DRBOP [6] . A second algorithm, called OM-DLBOP (One-to-Many Directed LMST Broadcast Oriented Protocol), is used instead of DLBOP when energy cost of one-to-one transmissions is too high (i.e. when network is dense). These two algorithms are combined in a hybrid protocol, called A-DLBOP (Adaptive Directed LMST Broadcast Oriented Protocol), which adaptively decides which communication model to use among one-to-one and one-to-many models. This protocol is energy-efficient and applied on general energy model (proposed in [6]) to optimize the energy consumption. Each node requires only the knowledge of neighbor positions. This information can be measured by using signal strength or time delay combined with direction evaluation by smart antennas. The position of each node can be also extracted with positioning system (like GPS).
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