Node Mobility

Mobility in wireless networks poses challenges because the links between nodes are continually changing. However, the changing of links can also be used to provide load balancing by rotating the set of nodes that form the gateway between the sink and the network. In theory, the sensor nodes could be moved around but since the nodes are resource constrained and the sink is not, it is usually the sink’s movement that is assumed.

Wang et al. considered the question of sink mobility in the context of a square network with the nodes distributed in a grid and with a single sink that can move to share location with any of the sensor nodes [WBMP05]. The sink visits every point in the grid once for a varying period of time and they calculated how much time the sink should spend at each point, allowing for zero time to be spent at some positions.

To simplify the problem Wang et al. assumed that the sink can move from one position to another instantaneously and designed a linear program which takes as its inputs the power consumption rates for every node while the sink is at every potential position. The rates depend on the routing protocol that is used and

they considered a protocol in which the packet is routed along the perimeter of a rectangle connecting the source node and the sink as illustrated by Fig. 2.4.

When the source node is not on the same row or column as the sink then two routes exist and packets are divided evenly between the two paths.

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Figure 2.4: The routing protocol considered by Wang et al. finds the two paths that form a rectangle connecting the source node and the sink and divides the traffic flow evenly between them. Illustration adapted from [WBMP05].

Simulations results from Wang et al. found that the sink should spend the longest time in the corners of the network followed by some time in an inner square, as shown in Fig. 2.5. The pattern of the stops follows from the routing protocol and different routing choices would result in different stops.

Around the same time as Wang et al., Luo and Hubaux were considering the same approach but for a circular network [LH05]. They first proved that, in terms of both latency and energy efficiency, the best single position for the sink is the centre of the network because as the sink moves away from the centre the maximum number of hops between a node and the sink increases. When the sink is at one edge of the network the worst case latency is double what it would be if the sink were at the centre. These extra hops not only increase latency but also result in more energy being consumed to forward packets to the sink.

However, Luo and Hubaux confirmed that the static sink causes imbalance in the work load and therefore that mobility can extend the lifetime of the network.

They examined the question of what the optimum mobility strategy would be for a circular network and concluded that it was for the sink to move along the outer circumference of the network which, according to their simulation results, would

2.2. SOLVING THE ENERGY HOLE PROBLEM 45

Figure 2.5: With the routing protocol used by Wang et al., a mobile sink should spend the largest time in the corners and an inner square in order to maximise the lifetime of the network. Figure taken from [WBMP05].

reduce the workload of the heaviest loaded node by about 80% compared to a network with a static, central sink.

Basagni et al. argued that centralised approaches (such as the linear program of Wang et al.) are too costly both in terms of computation time and energy usage to be feasible in wireless sensor networks [BCM⁺08]. They therefore pro-posed a distributed method for controlling the mobility of the sink which they called Greedy Maximum Residual Energy (GMRE) in which the sink is effectively

“drawn” to energy rich areas of the network. The network contains a number of sink sites arranged in a regular grid and the sink appoints nodes close to the sites to act as sentinels that monitor the available energy of the area and keep the sink informed. The sink can then make decisions about whether an alternative site has more energy available than its current one. Simulation results show that this technique can increase network lifetime by up to 350% compared to a static sink.

Yun and Xia [YX10] added another facet to the discussion by investigating a delay-tolerant network in which nodes are able to store a certain number of pack-ets before forwarding them to the sink. This allows each node to wait until the sink is closer to it before sending its packets. They found that the network lifetime increased linearly with the number of sink locations and, in the best case, every node can delay its transmissions until the sink is in direct transmission range.

In this case there is no need for routing or relaying and inter-corona balance is achieved as every node only transmits packets which are generated locally and at

the same rate for all nodes.

While sink mobility is a powerful method for maximising inter-corona balance there are potentially large costs associated with making the sink mobile. These energy costs have not been considered in the works cited in this section. Moreover, some terrains make a mobile sink (at least on the ground) extremely difficult.

Finally, controlling the sink’s mobility requires global knowledge of the network and significant overhead in terms of communication between nodes. For these reasons, sink mobility is not always a viable solution to the inter-corona balance problem.