Analysis of routing protocols and interference-limited communication in large wireless networks via continuum modeling

This paper investigates the speed limit of information propagation in large wireless networks, which provides fundamental understanding of the fastest information transportation and delivery that a wireless network is able to accommodate. We show that there is a unified speed upper bound for broadcast and unicast communications in large wireless networks. When network connectivity and successful packet delivery are considered, this speed upper bound is a function of node density. As this bound is unreachable with finite node density, we also quantify the gap between the actually achieved speed and the desired upper bound, which converges to zero exponentially as the node density increases to infinity.

This paper investigates the potential gain of cooperation in large wireless networks with multiple sources and relays, where the nodes form an homogeneous Poisson point process. The source nodes may choose their nearest neighbor from the set of inactive nodes as their relay. Although cooperation can potentially lead to significant improvements on the asymptotic error probability of a communication pair, relaying causes additional interference in the network, increasing the average noise. We address the basic question: how should source nodes optimally balance cooperation vs. interference to guarantee reliability in all communication pairs. Based on the decode-and-forward (DF) scheme at the relays, we derive closed-form approximations to the upper bounds on the error probability, averaging over all node positions. Surprisingly, in the small outage probability regime, there is an almost binary behavior that dictates — depending on network parameters — the activation or not of all relay nodes.

Previous results show that a node's throughput scales poorly as the network size increases when every node has traffic. However, in many cases, only a fraction of nodes in large networks have data to send or receive at any given time, while other nodes can act as relays/routers. Therefore, in this paper, we study the scaling behavior from a user's viewpoint (a user is a node with traffic). We first derive an upper bound on per user throughput. To derive the lower bound, we propose a simple scheduling scheme that enables users to cooperate with relay nodes and fully utilize the networks capacity. We show that per user throughput depends on the network size, the number of users, and the node deployment schemes, and is in general much more optimistic. Our scheme also sheds light on designing efficient cooperation protocols in heterogeneous networks and cognitive radio networks.

An efficient networks’ energy consumption and Quality of Services (QoS) are considered the most important issues, to evaluate the route quality of the designed routing protocol in Wireless Sensor Networks (WSNs). This study is presented an evaluation performance technique to evaluate two routing protocols: Secure for Mobile Sink Node location using Dynamic Routing Protocol (SMSNDRP) and routing protocol that used K-means algorithm to form Data Gathered Path (KM-DGP), on small and large network with Group of Mobile Sinks (GMSs). The propose technique is based on QoS and sensor nodes’ energy consumption parameters to assess route quality and networks’ energy usage. The evaluation technique is conducted on two routing protocols in two phases: The first phase is used to evaluate the route quality and networks’ energy consumption on small WSN with one mobile Sink Node (SN) and GMSs. The second phase, is used to evaluate the route quality and networks’ energy consumption on large network (four WSNs) with GMSs. The two phases are implementated by creating five sceneries via using NS2.3 simulator software. The implementation results of the proposed performance evaluation technique have demonstrated that SMSNDRP gives better networks’ energy consumption on small single network in comparison with KM-DGP. Also, it gives high quality route in large network that used four mobile SN, in contrast to KM-DGP that used sixteen mobile SNs. While in large network, it found that KM-DGP with sixteen mobile SNs gives better networks’ energy consumption in comparison with SMSNDRP with four mobile SNs.

Finding a number of nodes that are able to maximize the spread of influence through the social network and are called influence maximization has numerous applications in marketing. One such application is to find influential members for promoting a product across a large network. Even though numerous algorithms have been proposed, challenges such as scalability, time constraints, and low accuracy have motivated the researchers for better solutions. Some of the newly proposed algorithms are scalable, but fail to provide adequate accuracy. On the other hand, some greedy algorithms provide a good level of accuracy but are very time consuming for large networks. In this paper, an algorithm is proposed called FAIMCS that can quickly find influential nodes across large networks with high accuracy. FAIMCS, reduces computational overhead considerably by eliminating major portions of the social network graph which have little influence. FAIMCS uses community detection algorithm to determine each community's quota of influential nodes based on the structure of that community. Finally, it obtains influential nodes from the candidate nodes. Experiment results show FAIMCS is faster than current algorithms and provides a high level of accuracy for large social networks.

Mobile phone calling is one of the most widely used communication methods in modern society. The records of calls among mobile phone users provide us a valuable proxy for the understanding of human communication patterns embedded in social networks. Mobile phone users call each other forming a directed calling network. If only reciprocal calls are considered, we obtain an undirected mutual calling network. The preferential communication behavior between two connected users can be statistically tested and it results in two Bonferroni networks with statistically validated edges. We perform a comparative analysis of the statistical properties of these four networks, which are constructed from the calling records of more than nine million individuals in Shanghai over a period of 110 days. We find that these networks share many common structural properties and also exhibit idiosyncratic features when compared with previously studied large mobile calling networks. The empirical findings provide us an intriguing picture of a representative large social network that might shed new lights on the modelling of large social networks.

It has been a challenge to develop efficient algorithms for relay selection and relay power optimization in arbitrarily large multi-hop wireless networks. In this paper, considering Gaussian networks with half-duplex decode-and-forward relays, we develop a practical network-wide signal processing procedure with which the relay's data rate is not degraded by mutual interference. Multi-hop relaying is thus immune to mutual interference. Then, we develop an algorithm to find approximately the optimal hop count and the optimal relays for source-destination transmission rate maximization. With a quadratic complexity O(N2), where N is the network size, this algorithm is efficient for arbitrarily large wireless networks. More interestingly, this algorithm is similar to the well-known Dijkstra's algorithm of wired networks.

Parallel processing is a promising technique for reducing the execution time of a large and complex wireless network simulation. In this article, a parallel processing technique is presented for time-driven simulations of large and complex wireless networks. The technique explicitly considers the physical-layer details of wireless network simulators such as shadowing and co-channel interference. The technique uses multiple processors interconnected with highspeed links. Principles and issues are elaborated, including workload partitioning, synchronization, and database design. Numerical results from two different wireless network simulators employing the technique are presented to demonstrate the performance of the technique. The results indicate that the technique can significantly improve the run-time performance of time-driven simulations of large and complicated wireless networks of different types.

Large ad hoc networks, which are expected to become common in the Internet of Things, pose new scalability issues for traditional routing protocols. This study configures and compares HRAN, a routing protocol developed to scale to networks up to 1000 nodes, with traditional table based routing protocols for ad hoc networks. HRAN uses a specific type of bloom filter that is able to discard old elements, to store and disseminate topological information. The size and number of these structures is independent of the size or density of the network. Through simulation, we discover the suitable parameters for use on large networks, and compare HRAN with traditional table based routing protocols developed for mobile ad hoc environments.

Some applications of simulation require that the model state be advanced in simulation time than the wall-clock time advances as the simulation executes. This faster than requirement is crucial, for instance, when a simulation is used as part of a real-time control system, working through the consequences of contemplated control actions, in order to identify feasible (or even optimal) decisions. This paper considers the issue of than real-time simulation of very large communication networks, and how this is accomplished using our implementation (in C++) of the scalable simulation framework (SSF). Our tool (called iSSF) uses hierarchical levels of abstraction, and parallelism, to achieve speedups of nearly four orders of magnitude, enabling real-time execution rates on large network models. We quantify the effects that choice of hierarchical abstraction has on the simulation time advance rate, and show analytically and empirically how changing the abstraction mix affects performance.

Random geometric hypergraphs are considered as mathematical models of large wireless computer networks. The dependences of the mathematical expectation of the number of hyper-edges in random geometric hypergraphs on the radii of reliable reception / transmission of radio signals by network nodes, as well as on the number of vertices in the hyper- graph are studied. The concepts of the shortest route in a geometric hypergraph are discussed. Calculations of the probabil- ity of connectivity of large random geometric hypergraphs, the mathematical expectation of the diameter of hypergraphs and its change with a change in the radii of the nodes are carried out. The presentation of the results is accompanied by graphs.

SummaryThe paper deals with the modeling of memristors operating in extremely large memristive networks such as crossbar structures for memory and computational circuits, memristor‐based neural networks or circuits for massively parallel analog computations. Because the non‐convergence and other numerical problems increase with increasing complexity of the simulated circuit, suitable models of the individual memristors need to be choicely developed and optimized. Three different models are considered, each representing a specific trade‐off between speed and accuracy. Benchmark circuits for testing the applications of various complexities are used for the transient analysis in HSPICE. It is shown how the models can be modified to minimize the simulation time and improve the convergence. Copyright © 2017 John Wiley & Sons, Ltd.

We investigate the scalability of a class of algorithms that exploit the dynamics of wireless fading channels to achieve secret communication in a large wireless network of n randomly located nodes. We describe a construction in which nodes transmit artificial noise to suppress eavesdroppers whose locations are unknown and ensure secrecy of messages transported across the network. Under a model in which eavesdroppers operate independently and under appropriate conditions on the achievable per-node throughput Ψ(n), we show that the network can tolerate Ω((1⁄√n(n))2c) eavesdroppers while ensuring that the aggregate rate at which eavesdroppers intercept packets goes to 0, where c is a constant such that 0 0. We also establish sufficient conditions on the number of eavesdroppers to achieve a non-zero throughput in our construction.

In this paper we address the evaluation of speech quality through a wireless network as perceived by the user. User perceived evaluation (in addition to the usual network metrics including delay, throughput, packet loss statistics, etc.) is critical in the design of wireless multimedia networks where speech and video play a key role and are affected by several factors, such as network performance and encoding scheme. We use two approaches for our evaluation: small scale testbed implementation and hybrid simulation. The testbeds are implemented either by UDP (user datagram protocol) connection or UCLA talk connection. The hybrid simulation is event driven and is based on the Maisie parallel simulation language. It uses speech traces for inputs and plays back the speech outputs off-line. There are several advantages in using the simulation tool, mainly from the point of view of scalability and new protocol feature testing. At the same time, the real life testbed provides verification of the simulator assumptions, albeit on a small scale.

Nowadays, the existing myriad of wireless capable devices has led to the development of numerous multi-hop routing protocols. In particular, due to the scale of these networks, routing protocols with well defined hierarchies have been proposed. By defining different size scenarios with twenty different possible transitions in hierarchies for 2, 3 and 4 clusters, the impact of using such mechanism is evaluated. Simulation based results are presented for 2 different routing protocols showing that a Deferred Routing approach is able to successfully handle hierarchical transitions, delivering up to 4.5 times more data traffic than the remaining protocols, while maintaining a lower overhead. These results motivate the further utilization of such scheme for future large scale wireless networks.