TPR analysis

7.6.1 Minimum Energy Communication Network (MECN) Protocol

TheMECN protocol [Rod] is not specifically designed for sensor networks. However, the net-work model it proposes well suits WSNs. In fact, this is a distributed routing protocol where nodes are location-aware, i.e., equipped with a low-power global positioning system (GPS) [Sha], and periodically transmit to a master-site node (the sink). Synchronous communications are used, so that nodes can sleep between subsequent communications, thus lowering their duty cycle and power consumption. MECN aims to be a self-configuring routing protocol that minimizes energy

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Power-Efficient Routing in Wireless Sensor Networks 7-29

i k1

k2

k3 Relay

region

(a) (b)

Relay region boundary

Relay node r Transmit node i

Relay region asymptote

FIGURE . MECN regions. (a) Relay region of a transmit–relay node pair. (b) Representation of an enclosure.

(Redrawn from Shahani, A.R., Schaeffer, D.K., and Lee, T.H., A  mW wide dynamic range CMOS front-end for a portable GPS receiver, in Proceedings of IEEE International Solid-State Circuits Conference, vol. , pp. –, Feb.

.)

consumption for data forwarding by finding the minimum-power topology to route packets with.

In MECN the authors observe that with the most common channel model used for RF systems [Rap], the received power is proportional to /dⁿ, where d is the distance and n is the path loss exponent (with n ≥  for outdoor propagation models). Using this model, the transmission power required is not proportional to the covering range, so relaying data between nodes can be more energy-efficient than direct transmission. But considering the sensor field as a two-dimensional plane, it is possible to calculate whether direct transmission is more or less expensive than relay-ing as a function of the receiver’s position. Thus for each transmitter–relay node pair (i, r), a relay region can be defined as the region where forwarding through node r requires less energy than using direct transmission. A sample relay region is depicted in Figure .a. For each node i, the enclosure is defined as the union of the relay regions (i, n), with n ≠ i (depicted in Figure .b). This is the region around i beyond which it is not energy-efficient to perform forwarding, so it is not useful to take nodes into consideration for routing or to search for more neighbors. The main idea of this protocol is that, in order to find the minimum-energy path from a node to the sink, a very localized search can be performed that only considers nodes inside the enclosure.

Theprotocol is divided into two parts: a local search that finds the enclosure graph and minimum path construction. During the first phase, each node broadcasts a beacon containing its position and listens to beacons from neighbors. When it receives these messages, it computes the relay regions and only maintains nodes which do not lie in the relay regions of other neighbors. In this way the enclo-sure graph, which is the graph of communication links between all the nodes, is built. The second phase consists of finding optimal links in the enclosure graph. The algorithm adopted here is the distributed Bellman–Ford shortest path [Bel] [For], where power consumption is used as a cost metric.

Besides providing location information, GPS can also be used for synchronization purposes, so that nodes can synchronize their sleep and wake-up intervals. After a wake-up, a local search and minimum path construction have to be run in order to update optimal links. Hence the protocol is self-configuring and fault-tolerant, but requires a noticeable overhead. The protocol was extended

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7-30 Networked Embedded Systems

in [Li] with a computationally simpler algorithm which builds smaller subnetworks, thus providing lower link maintenance costs and less overhead. However, while this protocol minimizes power con-sumption for data forwarding, it does not maximize the overall network lifetime, which is usually the main target in WSN.

7.6.2 Geographic and Energy-Aware Routing (GEAR) Protocol

The GEAR protocol, described in [Yu], uses an energy-aware metric along with geographical information to efficiently disseminate data and queries across a WSN. Unlike other geographical pro-tocols not specifically devised for sensor networks, such as the well-known greedy perimeter stateless routing (GPSR) protocol [Kar], this protocol addresses the problem of forwarding data to each node inside a target region. This feature enables GEAR to support data-centric applications.

According to the GEAR protocol, each node has to know, besides its own location, the geographical position and residual energy of all its neighbor nodes. This can be accomplished through a low-frequency (and low-cost) hello message exchange. In addition, each query has to specify the target region, i.e., the area in which every node should receive the message. Each node maintains the learned costs, h(N, R), for each neighbor–region pair where packets have to be forwarded. First, when there is no h(N, R) entry for the neighbor N, this cost is computed as a function of the distance between N and the centroid of the region R and the energy consumed at node N. After the node has selected the next hop neighbor Nmin, the cost h(N, R) is set to h(Nmin, R)+C(N, Nmin), where the last term is the communication cost from N to the selected neighbor Nmin. The estimated cost can subsequently be updated through feedback from the receiver node. In fact, after each packet is delivered, the learned cost is sent back to the last hop. Thus, if the destination is reached with n hops, after n subsequent packets to the same target the correct cost is propagated to the source node. Thanks to this mechanism it is possible to avoid holes simply by forwarding packets to nodes with minimum learned costs. Thus, the forwarding rule when the target region is not reached is always to send data to the neighbor Ni

whose h(Ni, R) is minimum. If there are no holes, the learned cost will only represent a combination of consumed energy and distance, so it will be equivalent to the estimated cost. In the presence of a hole, on the other hand, the updated learned cost will act as a “resistance” to following the path toward that hole.

Since the objective of this protocol is to disseminate queries inside the target region R, data forwarding does not end when a packet reaches that region, as data must be forwarded to every node inside R. To efficiently achieve this behavior two different mechanisms are proposed, i.e., the Recursive Geographic Forwarding or the Restricted Flooding algorithm.

Recursive Geographic Forwarding is used when node density is high. This is a recursive approach in which if a node N receives a packet destined to its region R, it splits R into four different subregions, and sends four copies of the packet, each targeted at one of these subregions. The recursive algorithm terminates when the current receiver is the only node inside the target region. This algorithm works well when node density is high, but with low densities it is inefficient and in some cases can never terminate and keeps routing uselessly around an empty target region before the packet’s hop-count exceeds a certain bound. Thus when node density is low, the use of restricted flooding is suggested.

Restricted flooding exploits the broadcast medium of the wireless channel and only sends one broadcast message to all its neighbors, but every node in its transmission range receives this broadcast message whether it is an intended receiver or not.

This protocol achieves energy efficiency by means of the learned cost that takes residual energy into consideration along with geographical information about neighbors. By minimizing the energy cost between neighbors, an approximation of the lowest energy cost path is found. In order to improve network lifetime, the energy consumed so far is taken into account rather than the consumption of a single transmission. This protocol, compared with GSPR, features reduced energy consumption and a higher packet delivery ratio, at the expense of higher delay, as it takes longer paths in order to

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balance energy consumption. However, this protocol assumes negligible energy consumption in the idle state, and every node should always be active. Thus, if idle power consumption is high, energy dissipation in the idle state will dominate the total energy consumption. However, the protocol does not have particular requirements for the MAC layer, so the authors suggest the use of a low-power MAC that puts itself to sleep when no activity is required.