Search

The guard channel scheme in wireless mobile networks has attracted and is still drawing research interest owing to easy implementation and flexible control. Dynamic guard channel schemes have already been proposed in the literature to adapt to varying traffic load. This paper presents a novel control-theoretic approach to dynamically reserve guard channels called PI-Guard Channel (PI-GC) controller that maintains the handoff blocking probability (HBP) to a predefined value; while it still improves the channel resource utilization.

The guard channel scheme in wireless mobile networks has attracted and is still drawing research interest owing to easy implementation and flexible control. However guard channel schemes can not adapt to changing traffic loads because of static reserved guard channels. Therefore dynamic guard channel schemes have been proposed in the literature to adapt to varying traffic load. This paper presents a novel control-theoretic approach to dynamically reserve guard channels called PI-guard channel (PI-GC) controller. Experiments show that our proposed scheme can maintain the handoff blocking probability (HBP) to a predefined value while it still improves the channel resource utilization

Grid computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and high-performance orientation. A Grid integrates and coordinates resources and users that live within different control domains with the goal of delivering nontrivial quality of service (QoS). Consequently, task management and scheduling is of central importance for the Grid-based systems. In this paper, we model the task dispatching and selecting on the distributed Grid computing system by a multiserver multiqueue (MSMQ) model, and propose a modeling and analysis technique based on Stochastic Petri Net (SPN) methods. An approximate analysis technique is also proposed to reduce the complexity of the model.

Handoff is one of the key elements in ensuring quality of service (QoS) in mobile wireless networks. Handoff connections generally have higher priority than new connections. Traditional reservation policies that reserve some channels for handoff connections are not adaptive to traffic load changes. This paper proposes a new dynamic guard channel scheme (DGCS), which 1) adapts to various traffic loads; 2) combines differentiated QoS service model and priority handoff mechanism; 3) provides fairness for differentiated QoS services; 4) does not need to exchange state information among different cells, so it is easy to be implemented and is simple enough to be used in real time environments; 5) and utilizes network resources efficiently and puts a bound on each service blocking probability. The simulation results show that the ratios among different QoS service probabilities are guaranteed to be predefined values and system utilization is improved greatly.

Usually multiple quality of service (QoS) guarantees are required in most of multicast applications. In this paper, it is formulated as a multiobjective constrained combinatorial optimization problem for a protocol to determine multicast routes satisfying different QoS requirements. We use a multiobjective model and routing approach based on genetic algorithm that optimizes multiple QoS parameters simultaneously. The corresponding results demonstrate that the proposed approach is capable of discovering a set of nondominated routes within a finite evolutionary generation. Its feasibility and performance has been verified.

Recent advance-session based admission control (SBAC) has resulted in protecting the server from entering a regime in which latencies are excessive or session throughput collapses due to dropped requests and aborted sessions. The goal of this work is to introduce differentiated QoS to SBAC. We propose a two-threshold SBAC scheme (QSBAC). It can provide high throughput for preferred clients especially in overload situation. Furthermore, to adapt to varying traffic loads, a dynamic QSBAC (DQSBAC) scheme is also proposed. The experimental results show that comparing with SBAC scheme, both QSBAC scheme and DQSBAC scheme can sustain higher session throughput for preferred clients, as well as decrease aborted session percentage greatly. Comparing with QSBAC scheme, DQSBC scheme is more feasible because of its adaptation to varying traffic loads.

This paper proposed a sort of self-organizing IP QoS architecture based on adaptive edge control (QAAC) and presented its routing realization algorithms (called DSQR, distributed scalable QoS routing algorithm). In QAAC architecture, active probe would cooperate with passive regulate and artificial intelligence would control the proportion of probe packets, chromosome packets and information packets, in order to provide effective QoS for users. This architecture can enhance network adaptive and scalable through the user's adaptive and self-organizing behaving and QAAC will coexistence with traditional best effort services and architectures. The simulation results show that QAAC and DSQR are effective and applied to provide preferable service. This will accommodate the next generation network development and application requirements much more.