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In this paper, we propose a new Quality Link Metric (QLM), ``Inverse Expected Transmission Count (InvETX) in Optimized Link State Routing (OLSR) protocol. Then we compare performance of three existing QLMs which are based on loss probability measurements; Expected Transmission Count (ETX), Minimum Delay (MD), Minimum Loss (ML) in Static Wireless Multi-hop Networks (SWMhNs). A novel contribution of this paper is enhancement in conventional OLSR to achieve high efficiency in terms of optimized routing load and routing latency. For this purpose, first we present a mathematical framework, and then to validate this frame work, we select three performance parameters to simulate default and enhanc
Accurate representation of the physical layer is required for analysis and simulation of multi-hop networking in sensor, ad hoc, and mesh networks. This paper investigates, models, and analyzes the correlations that exist in shadow fading between links in multi-hop networks. Radio links that are geographically proximate often experience similar environmental shadowing effects and thus have correlated fading. We describe a measurement procedure and campaign to measure a large number of multi-hop networks in an ensemble of environments. The measurements show statistically significant correlations among shadowing experienced on different links in the network, with correlation coefficients up to 0.33. We propose a statistical model for the shadowing correlation between link pairs which shows strong agreement with the measurements, and we compare the new model with an existing shadowing correlation model of Gudmundson (1991). Finally, we analyze multi-hop paths in three and four node networks using both correlated and independent shadowing models and show that independent shadowing models can underestimate the probability of route failure by a factor of two or greater.
In Delay Tolerant Networks (DTNs), two-hop routing compromises energy versus delay more conveniently than epidemic routing. Literature provides comprehensive results on optimal routing policies for mobile nodes with homogeneous mobility, often neglecting signaling costs. Routing policies are customarily computed by means of fluid approximation techniques, which assure solutions to be optimal only when the number of nodes is infinite, while they provide a coarse approximation otherwise. This work addresses heterogeneous mobility patterns and multiple wireless transmission technologies; moreover, we explicitly consider the beaconing/signaling costs to support routing and the possibility for nodes to discard packets after a local time. We theoretically characterize the optimal policies by deriving their formal properties. Such analysis is leveraged to define two algorithmic approaches which allow to trade off optimality with computational efficiency. Theoretical bounds on the approximation guarantees of the proposed algorithms are derived. We then experimentally evaluated them in realistic scenarios of multi-class DTNs.
Recent advances in antenna technology have made the design of multi-beam antennas (MBA) feasible. Compared to an omni-directional or a single beam directional antenna, an MBA equipped node can achieve a throughput of up to m times, by simultaneously communicating on its m non-interfering beams. As a result, a few multi-beam directional medium access control (MAC) schemes have been proposed in the literature recently, which are implemented mostly on the in-house simulation setups in Matlab or C/C++. These implementations make many assumptions to simplify their design, without a thorough implementation of other network layers. However, the implementation of a multi-beam MAC scheme on the well-known discrete event network simulator platforms (such as the Riverbed Modeler, NS3, QualNet) is challenging as it requires extensive changes and additions to various source code modules. In fact, the network protocols in these simulator packages have been mainly designed for omni-directional communication, and very few implementations of directional MAC and other network protocols exist in the literature. This paper presents a framework to implement a multi-beam directional MAC scheme in multi-hop wireless networks, by using the Wireless Suite of Riverbed Modeler. The detailed implementation procedures are described for multi-beam antenna module, multi-beam node model, concurrent packet transmission and reception, scheduling, collision avoidance, retransmission, and local node synchronization. These MAC modules and methodology can be very helpful to the researchers and developers for implementing the single-beam as well as multi-beam directional MAC and routing protocols in Riverbed Modeler.
In this paper, we study the performance of greedy scheduling in multihop wireless networks, where the objective is aggregate utility maximization. Following standard approaches, we consider the dual of the original optimization problem. The dual can be solved optimally, only with the knowledge of the maximal independent sets in the network. But computation of maximal independent sets is known to be NP-hard. Motivated by this, we propose a distributed greedy heuristic to address the problem of link scheduling. We evaluate the effect of the distributed greedy heuristic on aggregate utility maximization in detail, for the case of an arbitrary graph. We provide some insights into the factors affecting aggregate utility maximization in a network, by providing bounds on the same. We give simulation results for the approximate aggregate utility maximization achieved under distributed implementation of the greedy heuristic and find them close to the maximum aggregate utility obtained using optimal scheduling.
Passive monitoring utilizing distributed wireless sniffers is an effective technique to monitor activities in wireless infrastructure networks for fault diagnosis, resource management and critical path analysis. In this paper, we introduce a quality of monitoring (QoM) metric defined by the expected number of active users monitored, and investigate the problem of maximizing QoM by judiciously assigning sniffers to channels based on the knowledge of user activities in a multi-channel wireless network. Two types of capture models are considered. The user-centric model assumes frame-level capturing capability of sniffers such that the activities of different users can be distinguished while the sniffer-centric model only utilizes the binary channel information (active or not) at a sniffer. For the user-centric model, we show that the implied optimization problem is NP-hard, but a constant approximation ratio can be attained via polynomial complexity algorithms. For the sniffer-centric model, we devise stochastic inference schemes to transform the problem into the user-centric domain, where we are able to apply our polynomial approximation algorithms. The effectiveness of our proposed schemes and algorithms is further evaluated using both synthetic data as well as real-world traces from an operational WLAN.