Distributed control algorithms for service differentiation in wireless packet networks

Abstract

Ab.sfracf-This paper investigates dlffenmtiated services in wireless packet networks using a fully distributed approach that supports service differentiation, radio monitoring and admission control. Service differ. entiation is based on the IEEE 802.11 Distributed Coordination Function (DCF) originally designed to support best-effort data services. We extend the Distributed Coordination Function to provide service differentiation for delay sensitive and best-effort traffic. Two distributed estimation algorithms are proposed and analyzed. A Virtual MAC (VMAC) algorithm passively monitors the radio channel and estimates locally achievable service levels. The Vk-hmt MAC estimates key MAC level statistics related to service quatity such as delay, delay variation, packet coltision and packet loss. We show the efficiency of the Virtuat MAC algontbm and consider significantly overlapping cells and highly bursty traffic mixes. A Virtual Source (VS) atgorithm utilizes the Virtual MAC to estimate application level service qmdity. The Vktuat Source allows application parameters to be tuned in response to dynamic channel conditions based on "virtnat delay curves". We demonstrate through simulation that when these distributed virtual algorithms are applied to the admission control of the radio channel then a globally stable state can be maintained without the need for complex centrtilzed radio resource management.Finally, we discuss a dktributed service level management scheme that builds on the proposed algorithms to offer continuous service with handoff.

IP Radio Resource Control System

“…Thus, we extend the work in [8] by recognizing the need to feedback time-varying conditions and not just congestion or flow-level performance, and further, by distinguishing local feedback conditions from global conditions in making proper resource and QOS policy decisions. We also extend the previous work by enabling more dynamic features across multiple layers and providing support for utility-based, adaptation (see [11], [12], [13]). This latter requirement allows the wireless application to adapt to either local SINR or global channel congestion feedback.…”

“…Moreover, through coordination with the RRM Agent acting as a local proxy, the IP QOS service can be (per application flow) configured through global policies algorithmically determined through bandwidth utility curves [11], [12] and managed by the centralized RRM. In this scenario, the RRM Agent obviates operational complexity between the various components, yet exposes necessary local methods and attributes allowing the layered components to coordinate with the Agent and communicate policies and state.…”

“…While noted progress has been made in the area of programmable wireless MACs [11] [12], [15], we adopt the notion of SINR utility curves [16] and apply this model towards differentiated access mechanisms supporting a programmable QOS link layer. Once again, through coordination with the RRM Agent, differentiated access can be (per application flow) dynamically (faster timescale) reconfigured through local policies algorithmically determined through SINR utility curves managed by the RRM Agent.…”

Static-Priority Scheduling of Sporadic Messages on a Wireless Channel

“…Some of these protocols [2,3,7] changed parameters in the IEEE 802.11 standard to be a function of deadlines, either choosing (i) inter-frame spacing (the amount of time that a station waits before transmitting) or (ii) the back-off times after a collision has occurred. These techniques are useful to meet deadlines because they can implement algorithms such as deadline monotonic [9].…”

“…Recently, the IEEE 802.11e profile was introduced with the intention of offering better support for Quality-of-Service. The previous approach [2,3,7] of choosing back-off times as a function of priorities was adopted, and the polling scheme in IEEE 802.11 was refined with traffic classes.…”