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The sensor placement problem considered by Biagioni and G Sasaki [31] is more dif cult They opt to nd a placement of nodes that achieves the coverage goals using the least number of sensors and also maintains a strongly connected network topology even if one node fails The authors review a variety of regular deployment topologies (eg, hexagonal, ring, star, etc) and study their coverage and connectivity properties under normal and partial failure conditions They argue that regular node placement simpli es the analysis due to their symmetry despite the fact that they often do not lead to optimal con guration The provided analytical formulation can be helpful in crafting a placement as a mix of these regular topologies and in estimating aggregate coverage of nodes Network connectivity is also a major concern when deploying sensor nodes.

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Unlike coverage, which has constantly been an objective or constraint for node placement, connectivity was deemed a non-issue in some of the early work based on the assumption that the transmission range Tr of a node is much longer than its sensing range Sr The premise is that good suf cient coverage will yield a connected network when Tr is multiple of Sr However, if the communication range is limited (eg, Tr = Sr ), connectivity becomes an issue unless there is a substantial redundancy in coverage It is worth noting that some work tackled the connectivity concern through deploying relay nodes that have long haul communication capabilities Such approaches will be discussed in detail later in this section Kar and Banerjee [32] considered sensor s placement for complete coverage and connectivity.

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This view of the access point capacity permits us to use the Erlang B formula to plot the call blocking probability as a function of the call arrival rate, In Figure 1210.

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Assuming that the sensing and radio ranges are equal, the authors rst de ne an r-strip as shown in Figure 97a In an r-stripe, nodes are placed so that neighbors of a sensor along the x-axis are located on the circumstance of the circle that de nes the boundary of its sensing and communication range Obviously, nodes on an r-strip are connected The authors then tile the entire plane with r strips on lines y = k(05 3 + 1)r such that the r-strips are aligned for even values of the integer k and shifted horizontally r/2 for odd values of k, as illustrated in Figure 97b The goal is to ll gaps in coverage with the least overlap among the r-disks that de ne the boundary of the sensing range.

TABLE 12.5. VoIP Capacities for IEEE 802.11e HCCA Codec G.711 G.726 G.729 802.11b 11 Mbps 16.1 17.8 19.3 802.11b 5.5 Mbps 12.7 14.8 17 802.11a 54 Mbps 105.6 120.7 135.3 802.11a 36 Mbps 89.3 106.1 123.6 802.11a 18 Mbps 60.9 77.9 98.3

To establish connectivity among nodes in different r-strips, additional sensors are placed along the yaxis, which marked by the shaded disks in Figure 107b For every odd value of the integer k, two sensors are placed at [0, k(05 3 + 1)r 05 3r] to establish connectivity between every pair of r-strips For a general convex-shaped nite-size region, connectivity among nodes in horizontal r-strips is established by another r-strip placed diagonally within the boundary of the region (Figure 97c) The authors generalize their scheme for the case where points of interest are to be covered rather than the whole area However, unless the base station is mobile and can interface with the WSN through any node, having a strongly connected network is not essential in WSNs since data are gathered at the base station.

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