Analytical models for capacity estimation of IEEE 802.11 WLANs using DCF for internet applications

We provide analytical models for capacity evaluation of an infrastructure IEEE 802.11 based network carrying TCP controlled file downloads or full-duplex packet telephone calls. In each case the analytical models utilize the attempt probabilities from a well known fixed-point based saturation analysis. For TCP controlled file downloads, following Bruno et al. (In Networking '04, LNCS 2042, pp. 626-637), we model the number of wireless stations (STAs) with ACKs as a Markov renewal process embedded at packet success instants. In our work, analysis of the evolution between the embedded instants is done by using saturation analysis to provide state dependent attempt probabilities. We show that in spite of its simplicity, our model works well, by comparing various simulated quantities, such as collision probability, with values predicted from our model. Next we consider N constant bit rate VoIP calls terminating at N STAs. We model the number of STAs that have an up-link voice packet as a Markov renewal process embedded at so called channel slot boundaries. Analysis of the evolution over a channel slot is done using saturation analysis as before. We find that again the AP is the bottleneck, and the system can support (in the sense of a bound on the probability of delay exceeding a given value) a number of calls less than that at which the arrival rate into the AP exceeds the average service rate applied to the AP. Finally, we extend the analytical model for VoIP calls to determine the call capacity of an 802.11b WLAN in a situation where VoIP calls originate from two different types of coders. We consider N-1 calls originating from Type 1 codecs and N-2 calls originating from Type 2 codecs. For G711 and G729 voice coders, we show that the analytical model again provides accurate results in comparison with simulations.

Fault-tolerant Video on Demand in RSerPool Architecture

With the advent of Internet, video over IP is gaining popularity. In such an environment, scalability and fault tolerance will be the key issues. Existing video on demand (VoD) service systems are usually neither scalable nor tolerant to server faults and hence fail to comply to multi-user, failure-prone networks such as the Internet. Current research areas concerning VoD often focus on increasing the throughput and reliability of single server, but rarely addresses the smooth provision of service during server as well as network failures. Reliable Server Pooling (RSerPool), being capable of providing high availability by using multiple redundant servers as single source point, can be a solution to overcome the above failures. During a possible server failure, the continuity of service is retained by another server. In order to achieve transparent failover, efficient state sharing is an important requirement. In this paper, we present an elegant, simple, efficient and scalable approach which has been developed to facilitate the transfer of state by the client itself, using extended cookie mechanism, which ensures that there is no noticeable change in disruption or the video quality.

An Efficient Distributed Scheme for Source Routing Protocol in Communication Networks

In this paper, we propose an efficient source routing algorithm for unicast flows, which addresses the scalability problem associated with the basic source routing technique. Simulation results indicate that the proposed algorithm indeed helps in reducing the message overhead considerably, and at the same time it gives comparable performance in terms of resource utilization across a wide range of workloads.

Traffic Profiling for Efficient Network Resource Utilization.

Traffic Engineering has been the prime concern for Internet Service Providers (ISPs), with the main focus being minimization of over-utilization of network capacity even though additional capacity is available which is under-utilized, Furthermore, requirements of timely delivery of digitized audiovisual information raises a new challenge of finding a path meeting these requirements. This paper addresses the issue of (a) distributing load to achieve global efficiency in resource utilization. (b) Finding a path satisfying the real time requirements of, delay and bandwidth requested by the applications. In this paper we do a critical study of the link utilization that varies over time and determine the time interval during which the link occupancy remains constant across days. This information helps in pre-determining link utilization that is useful in balancing load in the network Finally, we run simulations that use a dynamic time interval for profiling traffic and show improvement in terms number of calls admitted/blocked.

Experiences with a centralized scheduling approach for performance management of IEEE 802.11 wireless LANs

We present a centralized integrated approach for: 1) enhancing the performance of an IEEE 802.11 infrastructure wireless local area network (WLAN), and 2) managing the access link that connects the WLAN to the Internet. Our approach, which is implemented on a standard Linux platform, and which we call ADvanced Wi-fi Internet Service EnhanceR (ADWISER), is an extension of our previous system WLAN Manager (WM). ADWISER addresses several infrastructure WLAN performance anomalies such as mixed-rate inefficiency, unfair medium sharing between simultaneous TCP uploads and downloads, and inefficient utilization of the Internet access bandwidth when Internet transfers compete with LAN-WLAN transfers, etc. The approach is via centralized queueing and scheduling, using a novel, configurable, cascaded packet queueing and scheduling architecture, with an adaptive service rate. In this paper, we describe the design of ADWISER and report results of extensive experimentation conducted on a hybrid testbed consisting of real end-systems and an emulated WLAN on Qualnet. We also present results from a physical testbed consisting of one access point (AP) and a few end-systems.

Probabilistic Prediction based Scheduling for Delay Sensitive Traffic in Internet of Things

This paper proposes a probabilistic prediction based approach for providing Quality of Service (QoS) to delay sensitive traffic for Internet of Things (IoT). A joint packet scheduling and dynamic bandwidth allocation scheme is proposed to provide service differentiation and preferential treatment to delay sensitive traffic. The scheduler focuses on reducing the waiting time of high priority delay sensitive services in the queue and simultaneously keeping the waiting time of other services within tolerable limits. The scheme uses the difference in probability of average queue length of high priority packets at previous cycle and current cycle to determine the probability of average weight required in the current cycle. This offers optimized bandwidth allocation to all the services by avoiding distribution of excess resources for high priority services and yet guaranteeing the services for it. The performance of the algorithm is investigated using MPEG-4 traffic traces under different system loading. The results show the improved performance with respect to waiting time for scheduling high priority packets and simultaneously keeping tolerable limits for waiting time and packet loss for other services. Crown Copyright (C) 2015 Published by Elsevier B.V.