Social-Aware Forwarding Improves Routing Performance in Pocket Switched Networks

Several social-aware forwarding strategies have been recently introduced in opportunistic networks, and proved effective in considerably in- creasing routing performance through extensive simulation studies based on real-world data. However, this performance improvement comes at the expense of storing a considerable amount of state information (e.g, history of past encounters) at the nodes. Hence, whether the benefits on routing performance comes directly from the social-aware forwarding mechanism, or indirectly by the fact state information is exploited is not clear. Thus, the question of whether social-aware forwarding by itself is effective in improving opportunistic network routing performance remained unaddressed so far. In this paper, we give a first, positive answer to the above question, by investigating the expected message delivery time as the size of the net- work grows larger

Performance of ad hoc networks with two-hop relay routing and limited packet lifetime (extended version)

We consider a mobile ad hoc network consisting of three types of nodes (source, destination and relay nodes) and using the two-hop relay routing. This type of routing takes advantage of the mobility and the storage capacity of the nodes, called the relay nodes, in order to route packets between a source and a destination. Packets at relay nodes are assumed to have a limited lifetime in the network. Nodes are moving inside a bounded region according to some random mobility model. Closed-form expressions and asymptotic results when the number of nodes is large are provided for the packet delivery delay and for the energy needed to transmit a packet from the source to its destination. We also introduce and evaluate a variant of the two-hop relay protocol that limits the number of generated copies in the network. Our model is validated through simulations for two mobility models (random waypoint and random direction mobility models), and the performance of the two-hop routing and of the epidemic routing protocols are compared.\ud \u

Hybrid performance modelling of opportunistic networks

We demonstrate the modelling of opportunistic networks using the process algebra stochastic HYPE. Network traffic is modelled as continuous flows, contact between nodes in the network is modelled stochastically, and instantaneous decisions are modelled as discrete events. Our model describes a network of stationary video sensors with a mobile ferry which collects data from the sensors and delivers it to the base station. We consider different mobility models and different buffer sizes for the ferries. This case study illustrates the flexibility and expressive power of stochastic HYPE. We also discuss the software that enables us to describe stochastic HYPE models and simulate them.Comment: In Proceedings QAPL 2012, arXiv:1207.055

Autonomous Algorithms for Centralized and Distributed Interference Coordination: A Virtual Layer Based Approach

Interference mitigation techniques are essential for improving the performance of interference limited wireless networks. In this paper, we introduce novel interference mitigation schemes for wireless cellular networks with space division multiple access (SDMA). The schemes are based on a virtual layer that captures and simplifies the complicated interference situation in the network and that is used for power control. We show how optimization in this virtual layer generates gradually adapting power control settings that lead to autonomous interference minimization. Thereby, the granularity of control ranges from controlling frequency sub-band power via controlling the power on a per-beam basis, to a granularity of only enforcing average power constraints per beam. In conjunction with suitable short-term scheduling, our algorithms gradually steer the network towards a higher utility. We use extensive system-level simulations to compare three distributed algorithms and evaluate their applicability for different user mobility assumptions. In particular, it turns out that larger gains can be achieved by imposing average power constraints and allowing opportunistic scheduling instantaneously, rather than controlling the power in a strict way. Furthermore, we introduce a centralized algorithm, which directly solves the underlying optimization and shows fast convergence, as a performance benchmark for the distributed solutions. Moreover, we investigate the deviation from global optimality by comparing to a branch-and-bound-based solution.Comment: revised versio