Assessing and Redesigning Enterprise Networks through NS-2 to Support VoIP

AbstractIn the recent past, Voice over IP (VoIP) deployments over data networks are gaining popularity due to the massive growth in the broadband internet access. Successful deployment of these applications depends directly on the performance of the underlying data network. Based on this and the fact that today's data networks are operated to perform many significant applications, network administrators seek out a way to measure the impact of these applications on the existing network performance before deploying them. Occasionally, network redesign is necessity; considering redesign's alterations should preserve most of the existing network characteristics to reduce overall impact of deploying new applications in the network performance. In this paper, we evaluated readiness of the existing enterprise network through NS-2 to support VoIP and based on findings a solution for redesigning the enterprise network is proposed to enhance the new network performance and leaving sufficient capacity for future growth. We applied our approach on a medium size enterprise network as a case study, the results prove improvements in network performance after redesigning the existing enterprise network

On the Use of Iterative Approximations in Queueing Networks; with Simple Applications

Networks of queues which have a productform solution can be analyzed easily by the convolution method or with mean value analysis. Regrettably, however, many practical queueing network models do not possess a productform solution. In this paper the following approach is advocated for models with alight deviations from the productform conditions: approximate the model interatively by a sequence of models which satisfy conditions for simple analysis. Quite often aggregation and mean value analysis provide the natural approach for de signing an iteration step. Applications which are mentioned are: two-phase servers where the first phase is a preparatory one; a type of priorities; blocking; many-chains networks; FCFS-servers with different workloads for different types of customers

An Analytical Tool to Assess Readiness of Existing Networks for Deploying IP Telephony

Deploying IP telephony or voice over IP (VoIP) is a major and challenging task. This paper describes an analytical approach and tool to assess the readiness of existing IP networks for the deployment of VoIP. The analytical approach utilizes queueing network analysis and investigates two key performance bounds for VoIP: delay and bandwidth. The analytical tool is GUI-based and has an engine that automates the analytical approach. The engine determines the number of VoIP calls that can be sustained by a given generic network while satisfying VoIP QoS requirements and leaving adequate capacity for future growth. As a case study, the paper illustrates how the analytical tool can assess the readiness to deploy VoIP for a typical network of a small enterprise

Efficient partitioning and assignment on programs for multiprocessor execution

The general problem studied is that of segmenting or partitioning programs for distribution across a multiprocessor system. Efficient partitioning and the assignment of program elements are of great importance since the time consumed in this overhead activity may easily dominate the computation, effectively eliminating any gains made by the use of the parallelism. In this study, the partitioning of sequentially structured programs (written in FORTRAN) is evaluated. Heuristics, developed for similar applications are examined. Finally, a model for queueing networks with finite queues is developed which may be used to analyze multiprocessor system architectures with a shared memory approach to the problem of partitioning. The properties of sequentially written programs form obstacles to large scale (at the procedure or subroutine level) parallelization. Data dependencies of even the minutest nature, reflecting the sequential development of the program, severely limit parallelism. The design of heuristic algorithms is tied to the experience gained in the parallel splitting. Parallelism obtained through the physical separation of data has seen some success, especially at the data element level. Data parallelism on a grander scale requires models that accurately reflect the effects of blocking caused by finite queues. A model for the approximation of the performance of finite queueing networks is developed. This model makes use of the decomposition approach combined with the efficiency of product form solutions

An Analytic Approach for Deploying Desktop Videoconferencing

The deployment of desktop videoconferencing, also known as Video and Voice over IP (VVoIP), over existing IP networks is gaining popularity these days. Such a deployment has become a major and challenging task for data network researchers and designers. This paper presents an analytic approach for deploying videoconferencing. The approach utilizes queueing network analysis and investigates two key performance bounds for videoconferencing: delay and bandwidth. The approach can be used to assess the support and readiness of an existing IP network. Prior to the purchase and deployment of desktop videoconferencing equipment, the approach predicts the number of videoconferencing sessions or calls that can be sustained by an existing network while satisfying QoS requirements of all network services and leaving adequate capacity for future growth. As a case study, we apply our approach to a typical network of a small enterprise. In addition, we use OPNET network simulator to verify and validate our analysis. Results obtained from analysis and simulation are in line and give a close match

Two Analytical Models (with Infinite Buffer) for Evaluating Performance of Gigabit Ethernet Hosts

Two analytical models are developed to study the impact of interrupt overhead on operating system performance of network hosts when subjected to Gigabit network traffic. Under heavy network traffic, the system performance will be negatively affected due to interrupt overhead caused by incoming traffic. In particular, excessive latency and significant degradation in system throughput can be experienced. Also, user applications may livelock as the CPU power is mostly consumed by interrupt handling and protocol processing. In this paper, we present and compare two analytical models that capture host behavior and evaluate its performance. The first model is based on Markov processes and queueing theory, while the second, which is more accurate but more complex, is a pure Markov process. For the most part both models give mathematically-equivalent closed-form solutions for a number of important system performance metrics. These metrics include throughput, latency, stability condition, CPU utilizations of interrupt handling and protocol processing, and CPU availability for user applications. The analysis yields insight into understanding and predicting the impact of system and network choices on the performance of interrupt-driven systems when subjected to light and heavy network loads. More importantly, our analytical work can also be valuable in improving host performance. The paper gives guidelines and recommendations to address design and implementation issues. Simulation and reported experimental results show that our analytical models are valid and give a good approximation

Two Analytical Models (with Infinite Buffer) for Evaluating Performance of Gigabit Ethernet Hosts

Two analytical models are developed to study the impact of interrupt overhead on operating system performance of network hosts when subjected to Gigabit network traffic. Under heavy network traffic, the system performance will be negatively affected due to interrupt overhead caused by incoming traffic. In particular, excessive latency and significant degradation in system throughput can be experienced. Also, user applications may livelock as the CPU power is mostly consumed by interrupt handling and protocol processing. In this paper, we present and compare two analytical models that capture host behavior and evaluate its performance. The first model is based on Markov processes and queueing theory, while the second, which is more accurate but more complex, is a pure Markov process. For the most part both models give mathematically-equivalent closed-form solutions for a number of important system performance metrics. These metrics include throughput, latency, stability condition, CPU utilizations of interrupt handling and protocol processing, and CPU availability for user applications. The analysis yields insight into understanding and predicting the impact of system and network choices on the performance of interrupt-driven systems when subjected to light and heavy network loads. More importantly, our analytical work can also be valuable in improving host performance. The paper gives guidelines and recommendations to address design and implementation issues. Simulation and reported experimental results show that our analytical models are valid and give a good approximation

Two Analytical Models for Evaluating Performance of Gigabit Ethernet Hosts with Finite Buffer

Two analytical models are developed to study the impact of interrupt overhead on operating system performance of network hosts with limited-size or finite buffer. Under heavy network traffic such as that of Gigabit Ethernet, the system performance will be negatively affected due to interrupt overhead caused by incoming traffic. In particular, packet loss, excessive latency and significant degradation in system throughput can be experienced. Also, user applications may livelock as the CPU power is mostly consumed by interrupt handling and protocol processing. In this paper, we present and compare two analytical models that capture host behavior and evaluate its performance. The first model is based on Markov processes and queueing theory, while the second, which is more accurate but more complex, is a pure Markov process. The models yield equations for a number of important system performance metrics. These performance metrics include throughput, latency, packet loss, stability condition, CPU utilizations of interrupt handling and protocol processing, and CPU availability for user applications. Both models yield closed-form solutions and equations that are either mathematically equivalent or very closely matching. Our analysis yields insight into understanding and predicting the impact of system and network choices on the performance of interrupt-driven systems when subjected to light and heavy network loads. More importantly, our analytical work can also be valuable in improving host performance. The paper gives guidelines and recommendations to address design and implementation issues. Simulation and reported experimental results show that our analytical models are valid and give a good approximation