Distributed Dynamic Channel Allocation Research Articles

An effective channel allocation designed using hybrid memory dragonfly with imperialist competitive algorithm in distributed mobile adhoc network

SummaryThe channel availability problem reaches a higher degree in mobile ad hoc networks (MANETs) and garners a lot of attention in communication networks. Because increased mobile usage might result in a lack of channel allocation, an improved channel allocation technique is presented to tackle the availability problem. The distributed dynamic channel allocation (DDCA) model is built in this paper using the hybrid memory dragonfly with imperialist competitive (HMDIC) method. Based on optimization logic, this strategy assigns the channel to mobile hosts. The MANET provides a dispersed network within the coverage region in the absence of base station infrastructure. The HMDIC optimizer approach in this circumstance randomly begins every respective node to update and store their pbest value utilizing RAM dragonfly employing satellite images. The constraint values are then used to construct the cost function, which results in a strong kind of global optimum solution. The channels are therefore distributed in an effective manner. The HMDIC algorithm is used in this research to build a novel channel allocation system. It makes advantage of the exploration capabilities to successfully explore the individual node using MDA (Modified Dragonfly Algorithm) and locate the global best solution using imperialist competitive algorithm (ICA). Both of these combined tactics are more effective in accelerating the convergence of the allocation model. To validate the performance, the HMDIC‐based DDCA system provides promising results in terms of assigning available channels, thereby enhancing channel reuse efficiency and fractional interference.

QoS aware distributed dynamic channel allocation for V2V communication in TVWS spectrum

Vehicles use Dedicated Short Range Communication (DSRC) standard for communicating among themselves. But, with the increased number of on-road vehicles, DSRC channels get congested. So, an alternative to DSRC needs to be introduced, to meet the diverse demand for various vehicular applications. Federal Communication Commission released TV White Space (TVWS) for dynamic spectrum access. These TVWS channels has the potential to be used for Vehicle-to-Vehicle (V2V) communication. However, the vehicles are highly mobile and communicate in an adhoc manner. Thus, employing TVWS in V2V communication requires efficient optimized channel allocation technique. In this work, a distributed joint channel and power allocation technique is devised, that considers both spatio-temporal change of TVWS availability and vehicular mobility. The channels are allocated based on user's transmission requirement with an adjusted power level such that significant interference is not caused to neighbouring primary users and other secondary users, transmitting in the same channel. Multiple vehicles are assigned a single channel using the proposed optimization technique to increase the system throughput. Vehicles are enabled with cognitive facility that allows them to sense the spectrum availability instead of relying on the geo-location TVWS database. The optimized channel and power allocation problem is a Mixed Integer Non-Linear Programming model which is solved using Lagrange's dual method. Simulation analysis shows that proposed optimization technique achieves high throughput while maintaining the network's QoS.

DDCA in Cellular Network using Fuzzy rule based Multi-agent System

Present mobile networks have different Quality of Service (QoS) requirements to support increasing need with major objectives such as better admission control, effective bandwidth utilization, and fault tolerance. So the network aims at satisfying their demands without much degradation of quality in terms of call dropping and call blocking. It is possible by admission control algorithms and by optimizing the sharing and utilization of existing resources in an effective way. It improves the overall p erformance of the network system. This paper addresses different Quality of Service (QoS) requirements of the users of a cellular network with a focus on fuzzy based Call Admission Control Scheme (CAC) and optimized bandwidth allocation using M ulti Agent System M odel. We propose combined framework to address resource allocation problem. This problem can be dealt with the help of two issues in Admission control and Transmission control. The admission control – the decision to admit or reject the calls based on fuzzy logic control. Transmission control is provided thru Distributed Dynamic Channel allocation(DDCA) using co-operative negotiation of M ulti-Agent System. We demonstrate the efficiency of the proposed framework model by determining call dropping probability and call blocking probability.

A Distributed Dynamic Channel Allocation Scheme in Cellular Communication Networks

This article presents a description and performance evaluation of an efficient distributed dynamic channels allocation (DDCA) scheme, which can be used for channel allocation in cellular communication networks (CCNs), such as the global system for mobile communication (GSM). The scheme utilizes a well-known distributed artificial intelligence (DAI) algorithm, namely, the asynchronous weak-commitment (AWC) algorithm, in which a complete solution is established by extensive communication among a group of neighbouring collaborative cells forming a pattern, where each cell in the pattern uses a unique set of channels. To minimize communication overhead among cells, a token-based mechanism was introduced. The scheme achieved excellent average allocation efficiencies of over 85% for a number of simulations.

On distributed dynamic channel allocation in mobile cellular networks

Distributed dynamic channel allocation (DDCA) is a fundamental resource management problem in mobile cellular networks. It has a flavor of distributed mutual exclusion but is not exactly a mutual exclusion problem. We establish the exact relationship between the two problems. Specifically, we introduce the problem of relaxed mutual exclusion to model one important aspect of the DDCA problem. We develop a general algorithm that guarantees relaxed mutual exclusion for a single resource and prove necessary and sufficient conditions for the information structure. Considering distributed dynamic channel allocation as a special case of relaxed mutual exclusion, we apply and extend the algorithm to further address the issues that arise in distributed channel allocation such as deadlock resolution, dealing with multiple channels, design of efficient information structures, and channel selection strategies. Based on these results, we propose an example distributed channel allocation scheme using one of the information structures proposed. Analysis and simulation results are provided and show that the results of this research can be used to design more efficient distributed channel allocation algorithms.

Dynamic channel allocation techniques using adaptive modulation and adaptive antennas

This article studies the impact of adaptive quadrature amplitude modulation (AQAM) on network performance when applied to a cellular network, using adaptive antennas in conjunction with both fixed channel allocation (FCA) and locally distributed dynamic channel allocation (DCA) schemes. The performance advantages of using adaptive modulation are investigated in terms of the overall network performance, mean transmitted power, and the average network throughput. Adaptive modulation allowed an extra 51% of users to be supported by an FCA 4-QAM network, while in conjunction with DCA, an additional 54% user capacity was attained.

Distributed dynamic fault-tolerant channel allocation for cellular networks

Efficient allocation of communication channels is critical for the performance of cellular systems. The centralized channel allocation algorithms proposed in literature are neither robust nor scalable. Several of these algorithms are unable to dynamically adjust to spatial and temporal fluctuations in channel demand (load). We present a distributed dynamic channel allocation (DCA) algorithm in which heavily loaded regions acquire a large number of communication channels, while their lightly loaded neighbors get assigned fewer channels. As the spatial distribution of channel demand changes with time, the spatial distribution of allocated channels adjusts accordingly. The algorithm described in this paper requires minimal involvement of the mobile nodes, thus conserving their limited energy supply. The algorithm is proved to be deadlock free, starvation free, and fair. It prevents cochannel interference and can tolerate the failure of mobile as well as static nodes without any significant degradation in service. Simulation experiments demonstrate that the performance of the proposed distributed dynamic algorithm is comparable to, and for some metrics, better than that of efficient centralized dynamic algorithms where the central switch has complete and latest information about channel availability. The major advantages of the proposed algorithm over its dynamic centralized counterparts are its scalability, flexibility, and low computation and communication overheads.

Distributed dynamic channel allocation algorithms in microcells under light traffic loading

We consider distributed dynamic channel allocation (DCA) algorithms for wireless cellular networks. Two algorithm extremes are the baseline of our investigation: Theaggressive type algorithms, where channel assignments of ongoing calls may be reconfigured to make room for a new access request; and thetimid one, where reconfigurations are not permitted. While, generally, analyses of DCA algorithms appear very difficult, we show here that a light traffic analysis can be tractable. For that realm, we derive performance expressions showing significant reductions in access blocking probability when an aggressive, rather than the timid, access algorithms is used. The relative efficacy of various algorithms that we present can be analytically probed in this range. Certain aggressive algorithms are observed to attain the best performance possible therein. The advantage over timid is particularly substantial for planar cellular arrays. These results hint that there may be significant channel savings, associated with the type of aggressive algorithms described here, in the important, yet much more difficult to analyze, operating realm where the blocking, but not necessarily the loading, is low; and lead us to devise a family of hybrid DCA algorithms that are both stable and low blocking.

Simulation and performance analysis of dynamic channel allocation algorithms in DECT

Channel allocation is one of the fundamental problems faced by designers of the portable communication systems. A Distributed Dynamic Channel Allocation (DDCA) algorithm is proposed. The DDCA combines the advantages of both the fixed and the dynamic channel allocation algorithms in an effective way. Initialization is easy and it is adaptive to slowly changing environments. It is flexible. A port can utilize all the channels available to the system. It is adaptive to slowly changing environments so that the port can adjust the channel allocation automatically when ports are added or removed from the system. It is stable, simple and fully distributed. Simulation shows that it has 25% improvement over the UK DECT testbed DCA and 16% improvement over the Channel Segregation DCA in terms of system capacity with one percent of grade of service. >