Timothy A. Gonsalves

On the performance effects of station locations and access protocol parameters in Ethernet networks

A simulation study is presented in several distributions of stations on a linear-bus Ethernet. Aggregate performance is shown to depend on the distribution of stations. Individual station performance varies with the location of the station. Unbalanced distributions can lead to large performance differences between individual stations, with isolated stations achieving relatively poor performance compared to the average. The effects of access protocol parameters such as the number of buffers per station and the retransmission algorithm are examined. A modification of the standard retransmission algorithm is presented that enables a higher throughput to be achieved at high load. The results are compared to the predictions of theoretical models, and the applicability of the models to finite-population Ethernets is examined. >

Comparative performance of voice/data local area networks

Using simulation, a network-independent framework compares the performance of contention-based Ethernet and two contention-free round-robin schemes, namely Expressnet and the IEEE 802.4 token bus. Two priority mechanisms for voice/data traffic on round-robin networks are studied: the alternating-rounds mechanism of the Expressnet, and the token rotation timer mechanism of the token bus, which restricts access rights based on the time taken for a token to make one round. It is shown that the deterministic schemes almost always perform better than the contention-based scheme. Design issues such as the choice of minimum voice packet length, priority parameters, and voice encoding rate are investigated. An important aspect that is noted is the accurate characterization of performance over a wide region of the design space of voice/data networks. >

The role of technology in telecom expansion in India

It is not viable to expand the telecom network in India substantially at the prevalent level of per-line investment. However, systems based on new technologies, many developed in India, promise to more than halve the investment required. This article looks at the telecom scenario, the new technologies, the Indian products based on these technologies, and the cost reductions they promise. The provision of widespread Internet service with low access tariff is an important aspect of the new approach.

Detection of Syn Flooding Attacks using Linear Prediction Analysis

This paper presents a simple but fast and effective method to detect TCP SYN flooding attacks. Linear prediction analysis is proposed as a new paradigm for DoS attack detection. The proposed SYN flooding detection mechanism makes use of the exponential backoff property of TCP used during timeouts. By modeling the difference of SYN and SYN+ACK packets, we are successfully able to detect an attack within short delays. We use this method at leaf routers and firewalls to detect the attack without the need of maintaining any state

Employing Bayesian Belief Networks for energy efficient Network Management

Network Management Systems (NMS) are used to monitor the network and along with Operations Support Systems (OSS) maintain the performance with a focus on guaranteeing sustained QoS to the applications and services. One aspect that is given less importance is the energy consumption of the network elements during the off peak periods. This paper looks at a scenario where the NMS plays an important role in making the network energy efficient by intelligently turning the network elements or their selective ports to sleep mode when they are underutilized. To this end, we propose and evaluate a Bayesian Belief Network (BBN) based Decision Management System (DMS), which provides intelligent decisions to the NMS for it to adaptively alter the operational modes of the network elements, without compromising the performance and QoS constraints. Simulated network has been used to provide the proof of concept followed by discussions on the amount of energy saved and its effect on the network performance.

Packet-voice communication on an ethernet local computer network: an experimental study

Local computer networks have been used successfully for data applications such as file transfers for several years. Recently, there have been several proposals for using these networks for voice applications also. We describe a simple voice protocol for use on a packet-switching local network. This protocol is used in an experimental study of the feasibility of using a 3 Mbps experimental Ethernet network for packet-voice communications. The effect of various parameters on performance is examined. The study shows that with appropriately chosen parameters the experimental Ethernet is capable of supporting about 40 simultaneous 64-Kbps two-way voice conversations with acceptable quality. This corresponds to a utilization of 95% of the network capacity.

Performance characteristics of two Ethernets: an experimental study

Local computer networks are increasing in popularity for the interconnection of computers for a variety of applications. One such network that has been implemented on a large scale is the Ethernet. This paper describes an experimental performance evaluation of a 3 and a 10 Mb/s Ethernet. The effects of varying packet length and transmission speed on throughput, mean delay and delay distribution are quantified. The protocols are seen to be fair and stable. These measurements span the range from the region of high performance of the CSMA/CD protocol to the upper limits of its utility where performance is degraded. The measurements are compared to the predictions of existing analytical models. The correlation is found to range from good to poor, with more sophisticated models yielding better results than a simple one.

Mobile payment architectures for India

Mobile payments are a new and alternative payment method. Instead of using traditional methods like cash, cheque, or credit cards, a customer can use a mobile phone to transfer money or to pay for goods and services. Mobile payments have numerous advantages over traditional payment methods. Apart from their apparent flexibility, they enable consumers who do not have easy access to banking facilities to participate readily in financial transactions. Unfortunately, existing mobile payment solutions in India are not interoperable; i.e. they only offer services for merchants registered with them and do not allow the transfer of money to, or between, users of other payment providers. This limitation reduces the widespread adoption of mobile payments. In this paper, we propose new mobile payment architectures that support interoperability. A key technical aspect of the mobile payment process is to lookup customer details, for which we propose the following three design options: (1) a central database, (2) a peer-to-peer query, or (3) a hierarchical lookup. These options are evaluated using relevant metrics such as the complexity of implementation and scalability with respect to system size. Based on our evaluation we recommend that initially the peer-to-peer design is chosen, and once the technology is more widespread, the central database option should be adopted.

Detection of SYN flooding attacks using generalized autoregressive conditional heteroskedasticity (GARCH) modeling technique

This paper explores a fast and effective method to detect TCP SYN flooding attack. The Generalized autoregressive conditional heteroskedastic (GARCH) model which is the most commonly used statistical modeling technique for financial time series is proposed as a new technique for Denial of service attack detection. The exponential backoff and retransmission property of TCP during timeouts is exploited in the detection mechanism. We are able to detect low as well as high intensity SYN flooding attacks by modeling the difference between SYN and SYN+ACK packets using GARCH. Our studies show that this non linear volatility model performs better than earlier models like Linear Prediction.

Traffic modeling and classification using packet train length and packet train size

Traffic modeling and classification finds importance in many areas such as bandwidth management, traffic analysis, traffic prediction, network planning, Quality of Service provisioning and anomalous traffic detection. Network traffic exhibits some statistically invariant properties. Earlier works show that it is possible to identify traffic based on its statistical characteristics. In this paper, an attempt is made to identify the statistically invariant properties of different traffic classes using multiple parameters, namely packet train length and packet train size. Models generated using these parameters are found to be highly accurate in classifying different traffic classes. The parameters are also useful in revealing different classes of services within different traffic classes.