Junaid A. Khan

Performance and low power driven VLSI standard cell placement using tabu search

We engineer a well-known optimization technique namely tabu search (TS) (Sait and Youssef, 1999) for the performance and low power driven VLSI standard cell placement problem (Sait and Youssef, 1995; Minhas, 2001). The above problem is of multiobjective nature since three possibly conflicting objectives are considered to be optimized subject to the constraint of layout width. These objectives are power dissipation, timing performance, and interconnect wire length. It is well known that optimizing cell placement for even a single objective namely total wire length is a hard problem to solve. Due to the imprecise nature of objective values, fuzzy logic is incorporated in the design of the aggregating function. The above technique is applied to the placement of ISCAS-89 benchmark circuits and the results are compared with the Adaptive-bias Simulated Evolution (SimE) approach reported in (Youssef et al., 2001). The comparison shows a significant improvement over the SimE approach.

A fuzzy constraint-based routing algorithm for traffic engineering

We propose a low-complexity constraint-based routing algorithm for traffic engineering in packet networks that route end-to-end packet flows. The proposed fuzzy routing algorithm (FRA) modifies the well-known Dijkstras single-source shortest paths algorithm by using fuzzy-logic membership functions in the path-cost update process. The main objective of FRA is to reduce path-request blocking and increase overall network utilization. To achieve this objective, the algorithm computes new routes based on network-wide load balancing constraints. Simulation results show that FRA outperforms several earlier algorithms in terms of load balancing and path-request blocking.

Fuzzy aggregating functions for multiobjective VLSI placement

When fuzzy logic is used with multi-objective optimization, min/max operators may not be desirable. This is primarily due to the lack of compensation/submission of min/max. To overcome this, ordered weighted averaging (OWA) operators were proposed by R.R. Yager (1988). OWA requires the selection of a control parameter /spl beta/, which is different for different problem instances. In this paper, we propose new fuzzy aggregating functions that simulate the fuzzy AND/OR logic and that have the advantages of OWA without the need of any control parameter. A comparison with OWA for VLSI cell placement using simulated evolution produced encouraging results.

Fuzzy simulated evolution for power and performance optimization of VLSI placement

In this paper, an algorithm for VLSI standard cell placement for low power and high performance design is presented. This is a hard multiobjective combinatorial optimization problem with no known exact and efficient algorithm that can guarantee finding a solution of specific or desirable quality. Approximation iterative heuristics such as simulated evolution (SE) are best suited to perform an intelligent search of the solution space. SE comprises three steps, evaluation, selection and allocation. Due to imprecise nature of design information at the placement stage, the various objectives and constraints are expressed in fuzzy domain. The search is made to evolve towards a vector of fuzzy goals. In this work, a new method to calculate membership in evaluation stage is proposed. Selection stage is also fuzzified and a new controlled fuzzy operator is introduced. The proposed heuristics is compared with genetic algorithm (GA) and the proposed fuzzy operator is compared with fuzzy ordered weighted averaging operator (OWA). Fuzzified SE (FSE) with controlled fuzzy operators was able to achieve better solutions.

Traffic engineering with distributed dynamic channel allocation in BFWA mesh networks at millimeter wave band

Inherent difficulties in millimeter-wave radio operations, such as higher atmospheric attenuation, especially during rainy times, motivated the use of mesh architecture in millimeter-wave band for broadband fixed wireless access (BFWA) networks. When used with highly directional antennas, these mesh networks also provide better frequency reuse. In a recent proposed architecture for such networks, a link can have multiple radio channels. However, to provide traffic engineering with scalability, it is needed to develop a distributed dynamic channel allocation algorithm to allocate channels to these links. This paper proposes a distributed dynamic channel allocation algorithm that is scalable and able to provide traffic engineering if invoked periodically. The proposed solution provides traffic engineering by optimizing link capacities by adding or removing channels from a link while maintaining interference constraints, based on current network conditions. Simulation results suggested that proposed algorithm performs better than a solution based on fixed channel allocation

A traffic engineered routing algorithm based on fuzzy logic

This paper presents a routing algorithm that uses fuzzy logic to solve traffic engineering (TE) routing problem. Current TE routing algorithms are either inefficient or are too computationally expensive that these cannot be treated as practical solutions. The proposed algorithm performs better than many current TE routing algorithms and has time complexity equivalent to Dijkstras algorithm. Therefore it is suitable to be used in practical routers.

Fuzzified iterative algorithms for performance driven low power VLSI placement

In this paper we employ fuzzified simulated evolution and stochastic evolution algorithms for VLSI. standard cell placement targeting low power dissipation and high performance. Due to the imprecise nature of design information at the placement stage, the various objectives and constraints are expressed in fuzzy domain. The search is made to evolve towards a vector of fuzzy goals. The proposed algorithms are compared with genetic algorithm.

A fast constructive algorithm for fixed channel assignment problem

With limited frequency spectrum and an increasing demand for mobile communication services, the problem of channel assignment becomes increasingly important. It has been shown that this problem is equivalent to the graph-coloring problem, which is an NP-hard problem. In this work, a fast constructive algorithm is introduced to solve the problem. The objective of the algorithm is to obtain a conflict free channel assignment to cells which satisfies traffic demand requirements. The algorithm was tested on several benchmark problems, and conflict free results were obtained a within one second. Moreover, the quality of solution obtained was always same or better than the other reported techniques.

Fast force-directed/simulated evolution hybrid for multiobjective VLSI cell placement

VLSI standard cell placement is a hard optimization problem, which is further complicated with new issues such as power dissipation and performance. In this work, a fast hybrid algorithm is designed to address this problem. The algorithm employs simulated evolution (SE), an iterative search heuristic that comprises three steps: evaluation, selection and allocation. Solution quality is a strong function of the allocation procedure which is both time consuming and difficult. In this work a force directed approach in the allocation step of SE is used to both accelerate and improve the solution quality. Due to the imprecise nature of design information at the placement stage, objectives to be optimized are expressed in the fuzzy domain. The search evolves towards a vector of fuzzy goals. The proposed heuristic is compared with a previously presented SE approach. It exhibits significant improvement in terms of runtime for the same quality of solution.

Traffic Engineering in BFWA Mesh Networks at Millimeter Wave Band

Inherent difficulties in millimeter-wave radio operations, such as higher atmospheric attenuation, especially during rainy times, motivated the use of mesh architecture in millimeter-wave band for broadband fixed wireless access (BFWA) networks. When used with highly directional antennas, these mesh networks also provide better frequency reuse. A recent proposed architecture for such networks shows how a link can have multiple radio channels. This paper exploits this property to present a solution that uses distributed dynamic channel allocation (DDCA) to reconfigure the link capacities to achieve better Traffic Engineering. DDCA works by adding or removing channels from a link while satisfying interference constraints, based on current network conditions. The paper proposes a DDCA algorithm and then integrates it with routing. The distributed dynamic nature of the algorithm provides true scalability with fast and dynamic reconfiguration of the network. Simulation results show that the proposed solution provides better performance than solutions that employ a fixed channel allocation.