We study the novel hierarchical architecture of Mobile Backbone Networks. In such networks, a set of Mobile Backbone Nodes (MBNs), which are envisioned to be airborne, are deployed to provide an end-to-end communications capability for the terrestrial Regular Nodes (RNs). We address the joint problem of placing a fixed number K MBNs, and assigning each RN to exactly one MBN, using two optimization objectives. The first is the Maximum Fair Placement and Assignment (MFPA) problem in which the objective is to maximize the minimum throughput obtained by any RN. The second is the Maximum Throughput Placement and Assignment (MTPA) problem, in which the objective is to maximize the aggregate throughput of the RNs. We develop an optimal polynomial time algorithm for the MFPA problem for any K, and an optimal polynomial time algorithm for the MTPA problem for K≤ 2. We also develop lower complexity approximation algorithms and present simulation results comparing the performance of the various algorithms.

We study a novel hierarchical wireless networking approach in which some of the nodes are more capable than others. In such networks, the more capable nodes can serve as mobile backbone nodes and provide a backbone over which end-to-end communication can take place. Our approach consists of controlling the mobility of the backbone nodes in order to maintain connectivity. We formulate the problem of minimizing the number of backbone nodes and refer to it as the Connected Disk Cover (CDC) problem. We show that it can be decomposed into the Geometric Disk Cover (GDC) problem and the Steiner Tree Problem with Minimum Number of Steiner Points (STP-MSP). We prove that if these subproblems are solved separately by gamma- and delta-approximation algorithms, the approximation ratio of the joint solution is gamma+delta. Then, we focus on the two subproblems and present a number of distributed approximation algorithms that maintain a solution to the GDC problem under mobility. A new approach to the solution of the STP-MSP is also described. We show that this approach can be extended in order to obtain a joint approximate solution to the CDC problem. Finally, we evaluate the performance of the algorithms via simulation and show that the proposed GDC algorithms perform very well under mobility and that the new approach for the joint solution can significantly reduce the number of mobile backbone nodes.

We study the novel hierarchical architecture of Mobile Backbone Networks. In such networks, a set of mobile backbone nodes (MBNs) are deployed to provide an end-to-end communications capability for the regular nodes (RNs). In this work, we address the joint problem of placing a fixed number K MBNs in the plane, and assigning each RN to exactly one MBN. We formulate and solve two problems under a general communications model. The first is the maximum fair placement and assignment (MFPA) problem in which the objective is to maximize the throughput of the minimum throughput RN. The second is the maximum throughput placement and assignment (MTPA) problem, in which the objective is to maximize the aggregate throughput of the RNs. Our main result is a novel optimal polynomial time algorithm for the MFPA problem for fixed K. For a restricted version of the MTPA problem, we develop an optimal polynomial time algorithm for Kles2. We also develop two heuristic algorithms for both problems, including an approximation algorithm for which we bound the worst case performance loss. Finally, we present simulation results comparing the performance of the various algorithms developed in the paper.

We study a novel hierarchical wireless networking approach in which some of the nodes are more capable than others.In such networks,the more capable nodes can serve as Mobile Backbone Nodes and provide a backbone over which end-to-end communication can take place. Our approac consists of controlling the mobility of the Backbone Nodes in order to maintain connectivity. We formulate the problem of minimizing the number of backbone nodes and refer to it as the Connected Disk Cover problem.We show that it can be decomposed into the Geometric Disk Cover (GDC)problem and the Steiner Tree Problem wit Minimum Number of Steiner Points (STP-MSP). We prove that if these sub-problems are solved separately by γ- and δ- approximation algorithms, the approximation ratio of t e joint solution is γ + δ. Then, we focus on the two subproblems and present a number of distributed approximation algorithms that maintain a solution to the GDC problem under mobility A new approach to the solution of the STP-MSP is also described. We show that this approach can be extended in order to obtain a joint approximate solution to the Connected Disk Cover problem. Finally, we evaluate the performance of the algorithms via simulation and show that the proposed GDC algorithms perform very well under mobility and that the new approac for the joint solution can significantly reduce the number of required Mobile Backbone Nodes.

We develop algorithms for finding minimum energy disjoint paths in an all-wireless network, for both the node and link-disjoint cases. Our major results include a novel polynomial time algorithm that optimally solves the minimum energy 2 link-disjoint paths problem, as well as a polynomial time algorithm for the minimum energy k node-disjoint paths problem. In addition, we present efficient heuristic algorithms for both problems. Our results show that link-disjoint paths consume substantially less energy than node-disjoint paths. We also found that the incremental energy of additional link-disjoint paths is decreasing. This finding is somewhat surprising due to the fact that in general networks additional paths are typically longer than the shortest path. However, in a wireless network, additional paths can be obtained at lower energy due to the broadcast nature of the wireless medium. Finally, we discuss issues regarding distributed implementation and present distributed versions of the optimal centralized algorithms presented in the paper.