Proportional Differentiation Service Model Research Articles

Adaptive resource reservation schemes for proportional DiffServ enabled fourth-generation mobile communications system

Many mechanisms based on bandwidth reservation have been proposed in the literature to decrease connection dropping probability for handoffs in cellular communications. The handoff events occur at a much higher rate in packet-switched fourth generation mobile communication networks than in traditional cellular systems. An efficient bandwidth reservation mechanism for the neighboring cells is therefore critical in the process of handoff during the connection of multimedia calls to avoid the unwillingly forced termination and waste of limited bandwidth in fourth generation mobile communication networks, particularly when the handoff traffic is heavy. In this paper, two self-adaptive bandwidth reservation schemes, which adopt support vector regression and swarm intelligence techniques, respectively, are proposed to reduce the forced termination probability of multimedia handoffs. Meanwhile, a proportional differentiated service model is incorporated into our schemes to accommodate new metrics used in processing handoffs in next generation networks. The simulation results show that both the proposed schemes can achieve superior performance than the representative bandwidth-reserving schemes in the literature when performance metrics are measured in terms of the forced termination probability for the handoffs, the call blocking probability for the new connections and bandwidth utilization.

A new per-class flow fixed proportional differentiated service for multi-service wireless LAN

In this paper, we propose a new per-CLAss Flow fixed proportional differentiated service model (CLAF) and a companioning medium access control scheme for multi-service wireless LANs (WLANs), based on the IEEE 802.11 framework. Different from conventional relative differentiated service, in CLAF, a fixed bandwidth quality ratio is guaranteed on per-class per-flow basis regardless of the traffic load of each service class. Specifically, each service class is assigned a number of separate coordination periods, proportional to the policy-based bandwidth quality ratio for class isolation. Each class is associated with its own contention window size which is dynamically adjusted in accordance with the number of flows in the class in such a way to minimize collision probability between flows of the same class. Simulations results of the CLAF performance as well as a comparison with IEEE 802.11e EDCA including the support of QoS-sensitive VoIP applications are presented. The results show that the proposed scheme outperforms EDCA and achieves better resource utilization efficiency. CLAF can provide users a more predictive, affirmative service guarantees than conventional relative differentiated service like IEEE 802.11e EDCA.

Computing the loss differentiation parameters of the proportional differentiation service model

The proportional differentiation service model has emerged as a refined version of the DiffServ qualify of service (QoS) architecture. It relies on a series of parameters to enforce proportionally differentiated QoS criteria, such as queueing delay and packet loss. From the perspective of proportional loss differentiation, a large amount of work has been done on carrying out loss differentiation based on given parameters. Under certain network conditions, however, the loss differentiation cannot be met based on these hand picked parameters. While existing work focuses on enhancing dropping mechanisms themselves to honour the loss differentiation, the paper looks into calculating feasible differentiation parameters. By forming an optimisation problem based on multiple class blocking thresholds, the paper introduces a simple quantitative guideline to compute loss differentiation parameters. Derived closely related to network statuses and packet dropping mechanisms, these parameters ease the difficulty that dropping mechanisms may encounter when enforcing packet loss differentiation. Its finite computation time, moreover, makes practical implementation possible. Analytical and numerical results are given to substantiate the new approach and its merits.