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39
Wireless ad hoc networks with tunable topology
 In: Proceedings of the 45th Annual Allerton Conference on Communication, Control and Computing
, 2007
"... Abstract — We study the set of connectivity and topological ..."
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Abstract — We study the set of connectivity and topological
Globs in the Primordial Soup The Emergence of Connected Crowds in Mobile Wireless Networks
"... In many practical scenarios, nodes gathering at points of interest yield sizable connected components (clusters), which sometimes comprise the majority of nodes. While recent analysis of mobile networks focused on the process governing node encounters (“contacts”), this model is not particularly sui ..."
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In many practical scenarios, nodes gathering at points of interest yield sizable connected components (clusters), which sometimes comprise the majority of nodes. While recent analysis of mobile networks focused on the process governing node encounters (“contacts”), this model is not particularly suitable for gathering behavior. In this paper, we propose a model of stochastic coalescence (merge) and fragmentation (split) of clusters. We implement this process as a Markov chain and derive analytically the exact stationary distribution of cluster size. Further, we prove that, as the number of nodes grows, the clustering behavior converges to a mean field, which is obtained as a closedform expression. This expression translates the empirical merge and split rate of a scenario, a microscopic property, to an important macroscopic property—the cluster size distribution—with surprising accuracy. We validate all results with synthetic as well as realworld mobility traces from conference visitors and taxicabs with several thousand nodes.
Analysis of pernode traffic load in multihop wireless sensor networks
 IEEE Transactions on Wireless Communications
, 2009
"... Abstract—The energy expended by sensor nodes in data communication makes up a significant quantum of their total energy consumption. Consequently, a mathematical model that can accurately predict the communication traffic load of a sensor node is critical for designing efficient sensor network proto ..."
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Abstract—The energy expended by sensor nodes in data communication makes up a significant quantum of their total energy consumption. Consequently, a mathematical model that can accurately predict the communication traffic load of a sensor node is critical for designing efficient sensor network protocols. In this paper, we present an analytical model for estimating the pernode traffic load in a multihop wireless sensor network. We consider a typical scenario wherein, the sensor nodes periodically sense the environment and forward the collected samples to a sink using greedy geographic routing. The analysis incorporates the idealistic circular coverage radio model as well as a realistic model, lognormal shadowing. Our results confirm that irrespective of the radio model, the traffic load generally increases as a function of the node’s proximity to the sink. However, in the immediate vicinity of the sink, the two radio models yield quite contrasting results. The ideal radio model reveals the existence of a volcano region near the sink, where the traffic load drops significantly. On the contrary, with the lognormal shadowing model, the opposite effect is observed, wherein the traffic load actually increases at a much higher rate as one approaches the sink, resulting in the formation of a mountain peak. The results from our analysis are validated by extensive simulations. Index Terms—Traffic load, geographic routing protocols, sensor networks, multihop wireless networks. I.
CONSEL: Connectivitybased Segmentation in LargeScale 2D/3D Sensor Networks
"... Abstract—A cardinal prerequisite for the system design of a sensor network, is to understand the geometric environment where sensor nodes are deployed. The global topology of a largescale sensor network is often complex and irregular, possibly containing obstacles/holes. A convex network partition, ..."
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Abstract—A cardinal prerequisite for the system design of a sensor network, is to understand the geometric environment where sensor nodes are deployed. The global topology of a largescale sensor network is often complex and irregular, possibly containing obstacles/holes. A convex network partition, socalled segmentation, is to divide a network into convex regions, such that traditional algorithms designed for a simple geometric region can be applied. Existing segmentation algorithms highly depend on concave node detection on the boundary or sink extraction on the medial axis, thus leading to quite sensitive performance to the boundary noise. More severely, since they exploit the network’s 2D geometric properties, either explicitly or implicitly, so far there has been no general 3D segmentation solution. In this paper, we bring a new view to segmentation from a Morse function perspective, bridging the convex regions and the Reeb graph of a network. Accordingly, we propose a novel distributed and scalable algorithm, named CONSEL, for CONnectivitybased SEgmentation in Largescale 2D/3D sensor networks. Specifically, several boundary nodes first perform flooding to construct the Reeb graph. The ordinary nodes then compute mutex pairs locally, thereby generating the coarse segmentation. Next the neighbor regions which are not mutex pair are merged together. Finally, by ignoring mutex pairs which leads to small concavity, we provide the constraints for approximately convex decomposition. CONSEL is more desirable compared with previous studies: (1) it works for both 2D and 3D sensor networks; (2) it only relies on network connectivity information; (3) it guarantees a bound for the regions ’ deviation from convexity. Extensive simulations show that CONSEL works well in the presence of holes and shape variation, always yielding appropriate segmentation results. I.
On leveraging partial paths in partiallyconnected networks
 in: Proceeding of the 28th IEEE Conference on Computer Communications (INFOCOM), Rio de
, 2009
"... Mobile wireless network research focuses on scenarios at the extremes of the network connectivity continuum where the probability of all nodes being connected is either close to unity, assuming connected paths between all nodes (mobile ad hoc networks), or it is close to zero, assuming no multihop ..."
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Mobile wireless network research focuses on scenarios at the extremes of the network connectivity continuum where the probability of all nodes being connected is either close to unity, assuming connected paths between all nodes (mobile ad hoc networks), or it is close to zero, assuming no multihop paths exist at all (delaytolerant networks). In this paper, we argue that a sizable fraction of networks lies between these extremes and is characterized by the existence of partial paths, i.e., multihop path segments that allow forwarding data closer to the destination even when no endtoend path is available. A fundamental issue in such networks is dealing with disruptions of endtoend paths. Under a stochastic model, we compare the performance of the established endtoend retransmission (ignoring partial paths), against a forwarding mechanism that leverages partial paths to forward data closer to the destination even during disruption periods. Perhaps surprisingly, the alternative mechanism is not necessarily superior. However, under a stochastic monotonicity condition between current vs. future path length, which we demonstrate to hold in typical network models, we manage to prove superiority of the alternative mechanism in stochastic dominance terms. We believe that this study could serve as a foundation to design more efficient data transfer protocols for partiallyconnected networks, which could potentially help reducing the gap between applications that can be supported over disconnected networks and those requiring full connectivity. 1
1Connectivity of Confined Dense Networks: Boundary Effects and Scaling Laws
"... In this paper, we study the probability that a dense network confined within a given geometry is fully connected. We employ a cluster expansion approach often used in statistical physics to analyze the effects that the boundaries of the geometry have on connectivity. To maximize practicality and app ..."
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In this paper, we study the probability that a dense network confined within a given geometry is fully connected. We employ a cluster expansion approach often used in statistical physics to analyze the effects that the boundaries of the geometry have on connectivity. To maximize practicality and applicability, we adopt four important pointtopoint link models based on outage probability in our analysis: singleinput singleoutput (SISO), singleinput multipleoutput (SIMO), multipleinput singleoutput (MISO), and multipleinput multipleoutput (MIMO). Furthermore, we derive diversity and power scaling laws that dictate how boundary effects can be mitigated (to leading order) in confined dense networks for each of these models. Finally, in order to demonstrate the versatility of our theory, we analyze boundary effects for dense networks comprising MIMO pointtopoint links confined within a right prism, a polyhedron that accurately models many geometries that can be found in practice. We provide numerical results for this example, which verify our analytical results.
On the asymptotic connectivity of random networks under the random connection model
 in IEEE INFOCOM
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Article Medium Access Control for Opportunistic Concurrent Transmissions under Shadowing Channels
, 2009
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An Integrated Protocol for Maintaining Connectivity and Coverage under Probabilistic Models for Wireless Sensor Networks
 AD HOC & SENSOR WIRELESS NETWORKS VOL. 7, PP. 295–323
, 2009
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