This is a repository of personal notes from the fuzzy clustering literature. Parts of this document have been used in different manuscripts.
Arash Abadpour, Attahiru Sule Alfa, and Jeff Diamond, “Video Streaming using Overlay Networks”, Technical Report, Telecommunication Research Laboratories (TRLabs), 2008.
With the success of decentralized sharing of large files through peer–to–peer networks, commercial video streaming through overlay networks has become a point of interest, both in the academia and in the industry. This interest demands the no–guarantee peer–to–peer network to be redesigned in order to be used as reliable and controllable means of video delivery. In reaching this goal, thorough research on different network structures and video coding schemes has been carried out. As a result, discrete tree–based models have given their place to mesh networks which employ rateless coding. Therefore, models with focus on the individual connections have been replaced with networks which provide connection between sets of participating hosts. In this report, the literature of video streaming in overlay networks is briefly reviewed. Then, a network model is presented and solved. The report finishes with discussing the future directions of this research.
Arash Abadpour, Attahiru Sule Alfa, and Jeff Diamond, “Video-on-Demand Network Design And Maintenance Using Fuzzy Optimization”, Technical Report, Telecommunication Research Laboratories (TRLabs), 2007.
Video–on–Demand (VoD) is the entertainment source which, in the future, will likely overtake regular television. Even though many companies have deployed working VoD services, to reach to the foreseen potentials, aspects of the VoD should still undergo further improvement. An important aspect of a VoD system is the underlying network in which it operates. According to the huge number of customers in this network, it should be rigorously designed to fulfill performance criteria. This process should be able to find optimal locations for the nodes of the network as well as to determine the content which should be cached in each one. While, this problem is categorized in the general group of network optimization problems, its specific characteristics demand a new solution to be sought for it. In this paper, inspired by the good reputation of fuzzy optimization in similar problems in other fields, a fuzzy objective function is derived which is heuristically shown to minimize the communication cost in a VoD network, while also controlling the storage cost. Then, an iterative algorithm is proposed to find a locally optimal solution to the proposed objective function. Using the unrepeatable tendency of the proposed algorithm, a heuristic method for picking a good solution, from a bundle of solutions produced by the proposed algorithm, is also suggested. This paper includes formal statement of the problem and its mathematical analysis. Also, different scenarios in which the proposed algorithm can be utilized are discussed
Arash Abadpour, Attahiru Sule Alfa, and Anthony C.K. Soong, “A More Realistic Approach to Information-Theoretic Sum Capacity of Reverse Link CDMA Systems in a Single Cell”, University of Manitoba, 2006. (pdf) (html)
The information-theoretic approach to maximizing the aggregate capacity of the reverse link in a CDMA system looks for the best pattern of transmission power of the stations. In this framework, where the transmission from each station is noise to all others, extra constraints should be designed to lead to a practically applicable solution. The previous research has suggested a minimum guaranteed quality of service plus bounds on individual transmissions and the aggregate one. However, extensive analysis has revealed that these two constraints are not enough to produce a solution which can be realized in an actual system. Basically, lack of any constraint on neither the maximum capacity of each station nor the unfairness of the whole system has been found to be responsible for the partial solution in which all stations except for one are left to transmit at the lowest possible, while the selected station is served with a non-realistic bandwidth of couple of hundreds more. In this paper we devise a maximum capacity constraint and give an algorithm for solving the problem. Then, empirical evidence are analyzed to show that the system is actually becoming more even and practical when the new constraint is added.
Arash Abadpour, Attahiru Sule Alfa, and Anthony C.K. Soong, “Capacity-Share Controlled Information-Theoretic Sum Capacity of Reverse Link Single-Cell CDMA Systems”, University of Manitoba, 2006. (pdf)
By controlling the pattern of transmission powers of the stations in a CDMA system the aggregate capacity of the reverse link can be optimized. To make this problem practically applicable appropriate constraints should be added to it. In previous research bounds on transmission power, signal to noise ratio, and maximum capacity of single stations plus a maximum bound for the aggregate transmission power of the system were analyzed. However, none of these constraints controls the capacity share of single stations. Hence, we may reach to a transmission power pattern in which one third of the whole capacity is given to a single station. This increases the probability of the base station depending massively on one station, resulting in a major loss when that station stops transmission. In this paper we introduce another constraint into the available set. We reformulate the available problem by adding a maximum capacity share constraint and propose an algorithm for solving it. The paper includes mathematical analysis of the problem and experimental results.
A. Amirfazli, K. Khoshi, A. Yadollahi, Arash Abadpour, “Converting Industrial Drawings Type A to Type E from Non-Vector Form to Vector Form II”, Research Proceedings, Sharif University of Technology, 2000-2001, pp. 31-39.
R. Narimani, G. Bashiri, Arash Abadpour, “Gait Analysis by Image Processing”, Research Proceedings, Sharif University of Technology, 1999-2000, pp. 187-195.
A. Amirfazli, K. Khoshi, A. Yadollahi, Arash Abadpour, “Converting Industrial Drawings Type A to Type E from Non-Vector Form to Vector Form I”, Research Proceedings, Sharif University of Technology, 1999-2000, pp. 25-36.