Performance Of Large Networks Research Articles

Downlink Performance Analysis of Intelligent Reflecting Surface-Enabled Networks

Intelligent reflecting surfaces (IRSs) have been proposed as a promising technology to enhance signal transmissions in high-frequency bands. Up to now, the research on the performance of large networks with IRSs is still in its infancy. In this article, we study a Poisson bipolar network with line segment blockages and reflectors. By deriving the probability that an IRS can successfully reflect a signal from a transmitter to a receiver and the distribution of the distance traveled by the reflected signal, the performance impact of deploying IRSs on the signal propagation is investigated. The aggregated interference through reflective paths via IRSs is derived by modeling the IRSs as additional interfering sources with non-uniformly distributed interfering power in different directions. With these results, the signal-to-interference-and-noise ratio (SINR) and the achievable rate are further derived, where a characteristic function and the inverse theorem are adopted to handle the complicated channel fading of reflective signals. From the analysis, IRSs have a great potential to enhance the network performance, but the tradeoff between signal enhancement and reflective interference is important. That is, the performance gain suffers from a diminishing return with a large IRS fraction due to the growth of reflective interference.

The PDE Method for the Analysis of Randomized Load Balancing Networks

We introduce a new framework for the analysis of large-scale load balancing networks with general service time distributions, motivated by applications in server farms, distributed memory machines, cloud computing and communication systems. For a parallel server network using the so-called $SQ(d)$ load balancing routing policy, we use a novel representation for the state of the system and identify its fluid limit, when the number of servers goes to infinity and the arrival rate per server tends to a constant. The fluid limit is characterized as the unique solution to a countable system of coupled partial differential equations (PDE), which serve to approximate transient Quality of Service parameters such as the expected virtual waiting time and queue length distribution. In the special case when the service time distribution is exponential, our method recovers the well-known ordinary differential equation characterization of the fluid limit. Furthermore, we develop a numerical scheme to solve the PDE, and demonstrate the efficacy of the PDE approximation by comparing it with Monte Carlo simulations. We also illustrate how the PDE can be used to gain insight into the performance of large networks in practical scenarios by analyzing relaxation times in a backlogged network. In particular, our numerical approximation of the PDE uncovers two interesting properties of relaxation times under the SQ(2) algorithm. Firstly, when the service time distribution is Pareto with unit mean, the relaxation time decreases as the tail becomes heavier. This is a priori counterintuitive given that for the Pareto distribution, heavier tails have been shown to lead to worse tail behavior in equilibrium. Secondly, for unit mean light-tailed service distributions such as the Weibull and lognormal, the relaxation time decreases as the variance increases. This is in contrast to the behavior observed under random routing, where the relaxation time increases with increase in variance.

The PDE Method for the Analysis of Randomized Load Balancing Networks

We introduce a new framework for the analysis of large-scale load balancing networks with general service time distributions, motivated by applications in server farms, distributed memory machines, cloud computing and communication systems. For a parallel server network using the so-called $SQ(d)$ load balancing routing policy, we use a novel representation for the state of the system and identify its fluid limit, when the number of servers goes to infinity and the arrival rate per server tends to a constant. The fluid limit is characterized as the unique solution to a countable system of coupled partial differential equations (PDE), which serve to approximate transient Quality of Service parameters such as the expected virtual waiting time and queue length distribution. In the special case when the service time distribution is exponential, our method recovers the well-known ordinary differential equation characterization of the fluid limit. Furthermore, we develop a numerical scheme to solve the PDE, and demonstrate the efficacy of the PDE approximation by comparing it with Monte Carlo simulations. We also illustrate how the PDE can be used to gain insight into the performance of large networks in practical scenarios by analyzing relaxation times in a backlogged network. In particular, our numerical approximation of the PDE uncovers two interesting properties of relaxation times under the SQ(2) algorithm. Firstly, when the service time distribution is Pareto with unit mean, the relaxation time decreases as the tail becomes heavier. This is a priori counterintuitive given that for the Pareto distribution, heavier tails have been shown to lead to worse tail behavior in equilibrium. Secondly, for unit mean light-tailed service distributions such as the Weibull and lognormal, the relaxation time decreases as the variance increases. This is in contrast to the behavior observed under random routing, where the relaxation time increases with increase in variance.

Proportional Switching in First-in, First-out Networks

We consider a family of discrete time multihop switched queueing networks where each packet moves along a fixed route. In this setting, BackPressure is the canonical choice of scheduling policy; this policy has the virtues of possessing a maximal stability region and not requiring explicit knowledge of traffic arrival rates. BackPressure has certain structural weaknesses because implementation requires information about each route, and queueing delays can grow super-linearly with route length. For large networks, where packets over many routes are processed by a queue, or where packets over a route are processed by many queues, these limitations can be prohibitive. In this article, we introduce a scheduling policy for first-in, first-out networks, the ProportionalScheduler, which is based on the proportional fairness criterion. We show that, like BackPressure, the ProportionalScheduler has a maximal stability region and does not require explicit knowledge of traffic arrival rates. The ProportionalScheduler has the advantage that information about the network’s route structure is not required for scheduling, which substantially improves the policy’s performance for large networks. For instance, packets can be routed with only next-hop information and new nodes can be added to the network with only knowledge of the scheduling constraints.

Performance Evaluation of Fault Tolerance Protocols in MANET

A mobile ad hoc network (MANET) is a collection of wireless mobile nodes communicating with each other using multi-hop wireless Links without any existing network infrastructure or centralized administration. It has been shown that using multiple paths to route messages between any sourcedestination pair of nodes (instead of using a single path) balances the load more evenly throughout the network. The common belief is that the same is true for ad hoc networks, i.e., multi-path routing balances the load significantly better than single-path routing. Our Protocol, called MPOLSR & MDART is a multipath routing protocol for MANET. In addition route recovery & loop detection are implemented in MPOLSR in order to improve quality of service regarding OLSR.MP-OLSR is suitable for mobile, large & dense network with large traffic & could satisfy critical multimedia applications with high on time constraints. While MDART is an efficient protocol which gives improved performance in large networks. MDART is an enhancement of shortest path routing protocol known as Dynamic Address Routing (DART).MDART discovers and stores multiple paths to the destination in the routing table. In this paper, we have compare and analysis the performance of proactive multipath routing protocols for MANET under different scenarios & metrices using NS-2.

Performance Modeling of MANET Interconnectivity

The proliferation of mobile wireless computing devices and the increasing usage of wireless networking have motivated substantial research in mobile ad hoc networks (MANETs). In addition, much has also been done to link autonomous MANETs to the Internet, and as MANETs become more prevalent, the need to interconnect multiple MANETs becomes increasingly important too. However, direct interconnection of MANETs has rarely been studied. In this paper, we first report an experimental study on the performance of interconnected MANETs running two different routing protocols, viz., the Ad hoc On-Demand Distance Vector (AODV) and Optimized Link State Routing (OLSR) protocols, which represent the two major categories, and show that with the use of multiple gateways, it is possible to viably interconnect multiple networks running different MANET routing protocols. We then follow with a simulation study to evaluate the performance in large networks, which not only validates the scalability of the proposed scheme, but also helps to identify various problems that were not apparent in small experimental networks.

How initial conditions affect generalization performance in large networks

Generalization is one of the most important problems in neural-network research. It is influenced by several factors in the network design, such as network size, weight decay factor, and others. We show here that the initial weight distribution (for gradient decent training algorithms) is one other factor that influences generalization. The initial conditions guide the training algorithm to search particular places of the weight space. For instance small initial weights tend to result in low complexity networks, and therefore can effectively act as a regularization factor. We propose a novel network complexity measure, which is helpful in shedding insight into the phenomenon, as well as in studying other aspects of generalization.

Operational statistics in the management of large distribution systems

In order to manage a large distribution system in the best manner, it is considered necessary to have comprehensive, accurate and up-to-date records of the number and types of equipment items in service, together with properly analysed records of their performance.With the advent of nationalisation of the supply industry in 1948, and the formation of a small number of large undertakings, it became possible to study the performance of large networks in a manner not previously possible. The paper gives details of the way in which the necessary data are collected, analysed and used in one Area Board. Details are given of some of the conclusions reached to date of some other problems which are being studied, and some observations are made on reliability and security of supplies.Although some problems do not lend themselves to analytical treatment of the type described, many do, and it is contended that a great deal of valuable information on design, construction, operation and maintenance of networks can be obtained from the analysis of properly compiled data.