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We consider the problem of jammer placement to partition a wireless network, where the network nodes and jammers are located in the real plane. In previous research, we found optimal and suboptimal jammer placements by reducing the search space for the jammers to the locations of the network nodes. In this paper, we develop techniques to find optimal jammer placements over all possible jammer placements in the real plane. Our approach finds a set of candidate jammer locations (CJLs) such that a jammer-placement solution using the CJLs achieves the minimum possible cardinality among all possible jammer placements in the real plane. The CJLs can be used directly with the optimal and fast, suboptimal algorithms for jammer placement from our previous work. 

Wireless communication systems are susceptible to both unintentional interference and intentional jamming attacks. For mesh and ad-hoc networks, interference affects the network topology and can cause the network to partition, which may completely disrupt the applications or missions that depend on the network. Defensive techniques can be applied to try to prevent such disruptions to the network topology. Most previous research in this area is on improving network resilience by adapting the network topology when a jamming attack occurs. In this paper, we consider making a network more robust to jamming attacks before any such attack has happened. We consider a network in which the positions of most of the radios in the network are not under the control of the network operator, but the network operator can position a few “helper nodes” to add robustness against jamming. For instance, most of the nodes are radios on vehicles participating in a mission, and the helper nodes are mounted on mobile robots or UAVs. We develop techniques to determine where to position the helper nodes to maximize the robustness of the network to certain jamming attacks aimed at disrupting the network topology. Using our recent results for quickly determining how to attack a network, we use the harmony search algorithm to find helper node placements that maximize the number of jammers needed to disrupt the network