Self-similar Least Action Walk Research Articles

Simulation of the self-similar least-action walk model

ABSTRACT Simulation of ad hoc networks requires the use of a realistic human mobility model to give credibility to computer-based performance evaluations. To this end, a number of models have appeared in the literature from which the self-similar least-action walk model (SLAW) stands out as an approach mainly intended to incorporate several statistical properties of human motion. Although it is generally accepted that this model is able to produce realistic traces, so far not enough attention has been given towards creating an implementation with an upfront clear design that is also reliable and computationally efficient. This paper addresses these issues by presenting the design, implementation, and validation of a SLAW simulator. This simulator follows the discrete-event simulation paradigm for generation of mobility traces and is flexible enough for incorporating future walker models. This simulator can be used, among other purposes, to perform computer-based studies of networking technologies where human mobility plays a major role.

A Study on Cluster Stabilization Strategies for Human-Driven MANETs

Clustering is a commonly used method to adequately manage the network resources provided by mobile ad hoc networks (MANETs). In order to work appropriately in these networks, clustering protocols integrate stabilizing strategies that cope with topological changes caused by node motion. Although there is a number of studies related to clustering, cluster stability remains as a critical feature that has been barely addressed. It is not known, for instance, how stability of clustering protocols is affected when network nodes move following human mobility patterns (human-driven MANETs). The aim of this paper is to explore this open issue in order to improve the performance of clustering protocols in a human-driven environment and, in this way, to advance MANET research one step toward the deployment of real networks. To this end, the performance of several stabilizing strategies is assessed considering a network scenario where nodes roam according to the self-similar least-action walk (SLAW) model, which integrates several statistical features of human motion. Additionally, this work proposes to classify the stabilizing strategies into clusterhead-election based strategies, strategies based on relaxed-validity policies and strategies controlling the number of clusters. Our findings show that clustering protocols have to integrate flexible policies in order to improve stability as well as strategies dealing with burst reaffiliations and big-sized clusters.

Performance Evaluation of Efficient Routing Protocols in Delay Tolerant Network under Different Human Mobility Models

Delay and/or Disruption-Tolerant Networking (DTN) is a novel communication prototype that can span across multiple networks and deal with unpredicted conditions in the Internet model.Delay-tolerant networks (DTNs) are partitioned wireless ad hoc networks with intermittent connectivity. Additional terminology in this family of dynamic networks includes disruption-tolerant networks, intermittently connected networks, and opportunistic networks. Routing of the packets in DTN is based on store-carry-and forward paradigm. In this paper, we study and analyze performance of well known PROPHET and Spray and Wait routing protocol, under different human mobility models such as Truncated Levy Walk mobility model (TLW),Self-similar Least Action Walk (SLAW) and Random way point (RWP) model. The MATLAB simulator is used in order to analyze the performance of these routing protocols.Simulation results illustrate that Spray and Wait significantly outperforms the PROPHET on aspects of delivery ratio, average delay and communication overhead.

SLAW: Self-Similar Least-Action Human Walk

Many empirical studies of human walks have reported that there exist fundamental statistical features commonly appearing in mobility traces taken in various mobility settings. These include: 1) heavy-tail flight and pause-time distributions; 2) heterogeneously bounded mobility areas of individuals; and 3) truncated power-law intercontact times. This paper reports two additional such features: a) The destinations of people (or we say waypoints) are dispersed in a self-similar manner; and b) people are more likely to choose a destination closer to its current waypoint. These features are known to be influential to the performance of human-assisted mobility networks. The main contribution of this paper is to present a mobility model called Self-similar Least-Action Walk (SLAW) that can produce synthetic mobility traces containing all the five statistical features in various mobility settings including user-created virtual ones for which no empirical information is available. Creating synthetic traces for virtual environments is important for the performance evaluation of mobile networks as network designers test their networks in many diverse network settings. A performance study of mobile routing protocols on top of synthetic traces created by SLAW shows that SLAW brings out the unique performance features of various routing protocols.