Modeling and Optimization in Mobile, Ad-Hoc and Wireless Networks 

About: Modeling and Optimization in Mobile, Ad-Hoc and Wireless Networks is an academic conference. The conference publishes majorly in the area(s): Wireless network & Wireless ad hoc network. Over the lifetime, 1325 publications have been published by the conference receiving 19122 citations.

Node Placement for Connected Coverage in Sensor Networks

Abstract: We address the problem of optimal node placement for ensuring connected coverage in sensor networks We consider two different practical scenarios In the first scenario, a certain region (or a set of regions) are to be provided connected coverage, while in the second case, a given set of n points are to be covered and connected For the first case, we provide solutions that are within a small factor of the optimum For the second case, we present an algorithm that runs in polynomial time, and guarantees a constant factor approximation ratio

Modelling incentives for collaboration in mobile ad hoc networks

Abstract: This paper explores a model for the operation of an ad hoc mobile network. The model incorporates incentives for users to act as transit nodes on multi-hop paths and to be rewarded with their own ability to send traffic. The paper explores consequences of the model by means of fluid-level simulations of a network and illustrates the way in which network resources are allocated to users according to their geographical position.

The Effect of Rumor Spreading in Reputation Systems for Mobile Ad-hoc Networks

Abstract: Mobile ad-hoc networks rely on the cooperation of nodes for routing and forwarding. For individual nodes there are however several advantages resulting from noncooperation, the most obvious being power saving. Nodes that act selfishly or even maliciously pose a threat to availability in mobile adhoc networks. Several approaches have been proposed to detect noncooperative nodes. In this paper, we investigate the effect of using rumors with respect to the detection time of misbehaved nodes as well as the robustness of the reputation system against wrong accusations. We propose a Bayesian approach for reputation representation, updates, and view integration. We also present a mechanism to detect and exclude potential lies. The simulation results indicate that by using this Bayesian approach, the reputation system is robust against slander while still benefitting from the speed-up in detection time provided by the use of rumors.

Dynamic Association for Load Balancing and Interference Avoidance in Multi-cell Networks

Abstract: In promising OFDMA systems, downlink signals originating from the same base station (BS) are orthogonal, while those from different BSs interfere with each other. As a consequence, inter-cell interference (ICI) becomes major performance degradation factor. Particularly, boundary users suffer from severe ICI in addition to the inherent near-far problem. To improve cell edge performances and support a more balanced data rate among all users, partial frequency reuse (PFR) and load-balancing schemes are investigated in this paper. We have formulated a utility maximization problem with network-wide proportional fairness (PF) as an objective in a multi-cell network with PFR. To solve this problem, we propose an offline optimal algorithm and also efficient online algorithms. Our online algorithms are based on simple inter/intra-handover and cell-site selection in which a metric is changed from the signal strength to the average throughput. Through extensive simulations, we demonstrate that our online algorithms can achieve network-wide PF very closely. Compared to the conventional system with a universal frequency reuse where a user is bound to the best signal strength base station, the proposed algorithms bring two types of performance gain: interference avoidance (IA) and load balancing (LB) gain. These gains improve the system performance, especially for users at the cell boundary.

Downlink capacity and base station density in cellular networks

Abstract: There have been a bulk of analytic results about the performance of cellular networks where base stations are regularly located on a hexagonal or square lattice. This regular model cannot reflect the reality, and tends to overestimate the network performance. Moreover, tractable analysis can be performed only for a fixed location user (e.g., cell center or edge user). In this paper, we use the stochastic geometry approach, where base stations can be modeled as a homogeneous Poisson point process. We also consider the user density, and derive the user outage probability that an arbitrary user is under outage owing to low signal-to-interference-plus-noise ratio or high congestion by multiple users. Using the result, we calculate the density of success transmissions in the downlink cellular network. An interesting observation is that the success transmission density increases with the base station density, but the increasing rate diminishes. This means that the number of base stations installed should be more than n-times to increase the network capacity by a factor of n. Our results will provide a framework for performance analysis of the wireless infrastructure with a high density of access points, which will significantly reduce the burden of network-level simulations.