Mobile multi-robot teams deployed for monitoring or search-and-rescue missions in urban disaster areas can greatly improve the quality of vital data collected on-site. Analysis of such data can identify hazards and save lives. Unfortunately, such real deployments at scale are cost prohibitive and robot failures lead to data loss. Moreover, scaled-down deployments do not capture significant levels of interaction and communication complexity. To tackle this problem, we propose novel mobility and failure generation frameworks that allow realistic simulations of mobile robot networks for large scale disaster scenarios. Furthermore, since data replication techniques can improve the survivability of data collected during the operation, we propose an adaptive, scalable data replication technique that achieves high data survivability with low overhead. Our technique considers the anticipated robot failures and robot heterogeneity to decide how aggressively to replicate data. In addition, it considers survivability priorities, with some data requiring more effort to be saved than others. Using our novel simulation generation frameworks, we compare our adaptive technique with flooding and broadcast-based replication techniques and show that for failure rates of up to 60 it ensures better data survivability with lower communication costs.
Significant research has been done to provide realistic mobility models for MANETs. Of particular relevance for our work are group mobility models, such as the ones presented in @cite_19 , @cite_14 , @cite_43 and @cite_49 . These can be used to model the robot mobility inside the areas defined in this paper, instead of the Random Waypoint Model used. Also, a model for realistic representation of the movement of civil protection units in a disaster area scenario was presented in @cite_23 . This study focused on a small scale operation area such as a collapsed building (hundreds of square meters) with a high network density and high reachability between nodes. Instead, our study considers large operation areas (tens of square kilometers) that include several small working areas (e.g., collapsed buildings) and nodes forming a fairly sparse network. Moreover, node failures during the operation reduce further network density and challenge data survivability.
@cite_14 @cite_19 @cite_43 @cite_23 @cite_49
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This paper provides a model that realistically represents the movements in a disaster area scenario. The model is based on an analysis of tactical issues of civil protection. This analysis provides characteristics influencing network performance in public safety communication networks like heterogeneous area-based movement, obstacles, and joining leaving of nodes. As these characteristics cannot be modeled with existing mobility models, we introduce a new disaster area mobility model. To examine the impact of our more realistic modeling, we compare it to existing ones (modeling the same scenario) using different pure movement and link-based metrics. The new model shows specific characteristics like heterogeneous node density. Finally, the impact of the new model is evaluated in an exemplary simulative network performance analysis. The simulations show that the new model discloses new information and has a significant impact on performance analysis. This paper presents an analysis of the behavior of mobile ad hoc networks when group mobility is involved. We propose four different group mobility models and present a mobility pattern generator, called grcmob that we designed to be used with the ns-2 simulator. Using 2k factorial analysis we determine the most representative factors for protocol performance. We then evaluate the performance of a dynamic source routing (DSR) based MANET, using both TCP and UDP data traffic. The results are compared with the classical random waypoint mobility model. It is shown that the number of groups parameter is more important than the number of nodes one and that the impact of the area size is almost negligible. We make also evident that the mix of inter- and intra-group communication has the strongest impact on the performance. Finally, it is evidenced that the presence of groups forces the network topology to be sparser and therefore the probability of network partitions and node disconnections grows. Mobile ad hoc networks (MANETs) are multihop networks that are capable of establishing communication in the absence of any pre-existing infrastructure. Due to frequent node mobility and unreliable wireless links, the network is characterized by unpredictable topological changes. For more robust and reliable communications, it is important that a mobile node anticipates address changes and predicts its future routes in the network. This Chapter describes prediction-based mobility management schemes for mobile ad hoc networks. We propose a Markov model-based mobility management scheme that provides an adaptive location prediction mechanism. We used simulation method to evaluate the prediction accuracy as well as the probability of making the correct predictions. The simulation results indicated that higher order Markov models have slightly greater prediction accuracy than lower order Markov models. However, the prediction accuracy decreases with increase in the probability of random movement both for network sizes and number of hops. The Mobile Ad Hoc Network (MANET) has emerged as the next frontier for wireless communications networking in both the military and commercial arena. Handbook of Mobile Ad Hoc Networks for Mobility Models introduces 40 different major mobility models along with numerous associate mobility models to be used in a variety of MANET networking environments in the ground, air, space, and or under water mobile vehicles and or handheld devices. These vehicles include cars, armors, ships, under-sea vehicles, manned and unmanned airborne vehicles, spacecrafts and more. This handbook also describes how each mobility pattern affects the MANET performance from physical to application layer; such as throughput capacity, delay, jitter, packet loss and packet delivery ratio, longevity of route, route overhead, reliability, and survivability. Case studies, examples, and exercises are provided throughout the book. Handbook of Mobile Ad Hoc Networks for Mobility Models is for advanced-level students and researchers concentrating on electrical engineering and computer science within wireless technology. Industry professionals working in the areas of mobile ad hoc networks, communications engineering, military establishments engaged in communications engineering, equipment manufacturers who are designing radios, mobile wireless routers, wireless local area networks, and mobile ad hoc network equipment will find this book useful as well.