Evaluation and Innovation in Opportunistic Networks


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ISLAM, Muhammad, 2011. Evaluation and Innovation in Opportunistic Networks

@phdthesis{Islam2011Evalu-12967, title={Evaluation and Innovation in Opportunistic Networks}, year={2011}, author={Islam, Muhammad}, address={Konstanz}, school={Universität Konstanz} }

2011-05-12T07:12:39Z Islam, Muhammad deposit-license Islam, Muhammad eng The presence of an increasing number of mobile devices has prompted the demand to use them for information dispersion through opportunistic networks, which they form coincidently due to their geographic location. Opportunistic networks pose several new challenges to the current transmission protocols as they are not only capable of store and forward routing, but also lack the offline routing capability, i.e. source and destination must be connected to the network simultaneously. We can find several opportunistic network protocols in literature, but neither a solid comparison nor a trusted baseline has been presented.<br />In this study, we have analyzed and evaluated eight existing routing algorithms on a common basis in an effort to grasp the strong and weak points of each of them and to see whether it is possible to design a hybrid technique that may take advantage of the strengths of several other techniques. We propose three important criticisms regarding the evaluation of existing routing algorithms.<br />1. Most evaluations restrict themselves to comparing against the two extremes, direct-contact forwarding and flooding.<br />2. Each attempt uses a completely different choice of scenario and simulation parameters.<br />3. Most attempts concentrate on methods to find a path to destination but the reliability of the path cannot be ensured in this paradigm.<br />The findings have revealed that almost all the techniques fail to perform under variable conditions, i.e. bandwidth hungry techniques failed to deliver when bot- tlenecks existed although, they outclassed every other technique where network had sufficient capacity. In contrast, techniques that required good network con- nectivity failed to perform in sparse network. As a result of our comparison of selected networks under a wide variety of realistic scenarios, we have not only been able to identify and describe favorable traits of protocols, but also neces- sary relationships of successful mobile opportunistic network protocols with QoS routing. This study defines a very light weight metric, which not only encapsu- lates the path bandwidth but also maintains a dynamic path ranking by degrading the path efficiency as it suffers from data load. Moreover, this study focuses on the routing algorithm Nile1 that has an adapting capability with the underlying network. It thereby maintains acceptable performance without exhausting the network resources keeping a check on the network “pulse”, i.e. bandwidth. Nile is a multi-path protocol that deploys replication based on heuristic for computing disjoint path . Flooding is considered to be a protocol that can deliver the best performance if its overhead is ignored. Therefore, it is customary to use flooding as a performance benchmark for opportunistic networks. We identify and describe the current sim- ulation practices that do not expose the shortcomings of flooding as an upper bound. We provide a step towards a routing benchmark, which is flexible, pro- vides results close to an upper bound, is simple to implement, and thus might be a candidate for a common benchmark. This new method called EPO2, does not suffer from bottlenecks that limit the performance of epidemic flooding, even when bandwidth is scarce. Our analysis shows that networks are not suffering congestion as suggested by flooding, giving a better insight in the underlying network.<br />Since most of the practical routing protocols rely on history to profile devices, these profiles are used to compute the routes in the network. We found that history is either not able to predict device behavior accurately or history looses the details about the device behavior due to aggregation of metrics. We have therefore analyzed opportunistic network with max-flow to see the throughput of the network. We afterwards compared the outcome of this max-flow with a modified max-flow that uses history for its throughput computations. We have found that it is not possible to obtain an accurate history based max-flow, since it is not easy to find the link in path that can be considered to be responsible if history gives an unreliable path. 2011-05-12T07:12:39Z 2011 Evaluation and Innovation in Opportunistic Networks

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