ESPN: Efficient server placement in probabilistic networks with budget constraint

Abstract

The notion of probabilistic network has been used to characterize the unpredictable environment in wireless communication networks or other unstable networks. In this paper, we are interested in the problem of placing servers in probabilistic networks subject to budget constraint, so as to maximize the expected number of servable clients that can successfully connect to a server. We study this problem in both the single-hop model and the multi-hop model. We discuss the computational complexity of this problem and show that it is NP-hard under both models. We then develop efficient approximation algorithms, which produce solutions provably close to optimal. If the costs of candidate locations are uniform, when extra budget is available in the future, the progressive feature of our algorithms allows for placing additional servers instead of relocating all the servers, while retaining the guaranteed performance. Results of extensive experiments on different topologies confirm the performance of our algorithms compared to the optimal algorithm and other heuristic algorithms.

On the 2-MRS Problem in a Tree with Unreliable Edges

“…According to (8) in Lemma 2, for any V ∈ ( ), we are sure that V is either in Q ( ) or in ( ), where is a child other than ( ) of some node in Q ( ). We can use (19) when = 1 and (20) when = 2 to compute F ( , ; V) if V ∈ Q ( ) and use (22) otherwise. Thus, for all ∈ \ { }, we have…”

“…In addition, the most reliable route problem has been studied in [9,14,19] and its delay-constrained version has been studied in [21]. Recently, the problem of placing servers [22] and the problem of assigning links [23] in probabilistic wireless networks have been considered. Also, the continuous data collection schemes have been proposed in probabilistic wireless sensor networks (WSNs) [24,25].…”