The network virtualization allows new on-demand management capabilities, in this work we demonstrate such a service, namely, on-demand efficient monitoring or anonymity. The proposed service is based on network virtualization of expanders or sparsifiers over the physical network. The defined virtual (or overlay) communication graphs coupled with a multi-hop extension of Valiant randomization based routing lets us monitor the entire traffic in the network, with a very few monitoring nodes. In particular, we show that using overlay network with expansion properties and Valiant randomized load balancing it is enough to place @math monitor nodes when the length of the overlay path (number of intermediate nodes chosen by Valiant's routing procedure) is @math . We propose two randomized routing methods to implement policies for sending messages, and we show that they facilitate efficient monitoring of the entire traffic, such that the traffic is distributed uniformly in the network, and each monitor has equiprobable view of the network flow. In terms of complex networks, our result can be interpreted as a way to enforce the same betweenness centrality to all nodes in the network. Additionally, we show that our results are useful in employing anonymity services. Thus, we propose monitoring or anonymity services, which can be deployed and shut down on-demand. Our work is the first, as far as we know, to bring such on-demand infrastructure structuring using the cloud network virtualization capability to existing monitoring or anonymity networks. We propose methods to theoretically improve services provided by existing anonymity networks, and optimize the degree of anonymity, in addition providing robustness and reliability to system usage and security. We believe that, our constructions of overlay expanders and sparsifiers weighted network are of independent interest.
We show that our network architecture is valuable for network monitoring. showed an efficient flooding scheme for generating a collaboration between a group of random walking agents who are released from different sources and at different times @cite_0 . This participation of agents results in a collaborative monitoring infrastructure, requiring only a small number of active monitors.
@cite_0
2146971820 2060660772 2152628545 2141435168
This paper presents Glossy, a novel flooding architecture for wireless sensor networks. Glossy exploits constructive interference of IEEE 802.15.4 symbols for fast network flooding and implicit time synchronization. We derive a timing requirement to make concurrent transmissions of the same packet interfere constructively, allowing a receiver to decode the packet even in the absence of capture effects. To satisfy this requirement, our design temporally decouples flooding from other network activities. We analyze Glossy using a mixture of statistical and worst-case models, and evaluate it through experiments under controlled settings and on three wireless sensor testbeds. Our results show that Glossy floods packets within a few milliseconds and achieves an average time synchronization error below one microsecond. In most cases, a node receives the flooding packet with a probability higher than 99.99 , while having its radio turned on for only a few milliseconds during a flood. Moreover, unlike existing flooding schemes, Glossy's performance exhibits no noticeable dependency on node density, which facilitates its application in diverse real-world settings. Flooding based querying and broadcasting schemes have low hop-delays of Theta(1 R(n)) to reach any node that is a unit distance away, where R(n) is the transmission range of any sensor node. However, in sensor networks with large radio ranges, flooding based broadcasting schemes cause many redundant transmissions leading to a broadcast storm problem. In this paper, we study the role of geographic information and state information (i.e., memory of previous messages or transmissions) in reducing the redundant transmissions in the network. We consider three broadcasting schemes with varying levels of local information where nodes have: (i) no geographic or state information, (ii) coarse geographic information about the origin of the broadcast, and (Hi) no geographic information, but remember previously received messages. For each of these network models, we demonstrate localized forwarding algorithms for broadcast (based on geography or state information) that achieve significant reductions in the transmission overheads while maintaining hop-delays comparable to flooding based schemes. We also consider the related problem of broadcasting to a set of "spatially uniform" points in the network (lattice points) in the regime where all nodes have only a local sense of direction and demonstrate an efficient "sparse broadcast" scheme based on a branching random walk that has a low number of packet transmissions. Thus, our results show that even with very little local information, it is possible to make broadcast schemes significantly more efficient. We consider Mobile Ad-hoc NETworks (MANETs) formed by n nodes that move independently at random over a finite square region of the plane. Nodes exchange data if they are at distance at most r within each other, where r > 0 is the node transmission radius . The flooding time is the number of time steps required to broadcast a message from a source node to every node of the network. Flooding time is an important measure of the speed of information spreading in dynamic networks. We derive a nearly-tight upper bound on the flooding time which is a decreasing function of the maximal velocity of the nodes. It turns out that, when the node velocity is "sufficiently" high, even if the node transmission radius r is far below the connectivity threshold , the flooding time does not asymptotically depend on r . So, flooding can be very fast even though every snapshot (i.e. the static random geometric graph at any fixed time) of the MANET is fully disconnected. Our result is the first analytical evidence of the fact that high, random node mobility strongly speed-up information spreading and, at the same time, let nodes save energy . This paper presents two efficient flooding algorithms based on 1-hop neighbor information. In the first part of the paper, we consider sender-based flooding algorithms, specifically the algorithm proposed by In their paper, propose a sender-based flooding algorithm that can achieve local optimality by selecting the minimum number of forwarding nodes in the lowest computational time complexity O(n logn), where n is the number of neighbors. We show that this optimality only holds for a subclass of sender-based algorithms. We propose an efficient sender-based flooding algorithm based on 1-hop neighbor information that reduces the time complexity of computing forwarding nodes to O(n). In Liu's algorithm, n nodes are selected to forward the message in the worst case, whereas in our proposed algorithm, the number of forwarding nodes in the worst case is 11. In the second part of the paper we propose a simple and highly efficient receiver-based flooding algorithm. When nodes are uniformly distributed, we prove that the probability of two neighbor nodes broadcasting the same messageneighbor nodes broadcasting the same message exponentially decreases when the distance between them decreases or when the node density increases. The analytical results are confirmed using simulation.