Achieving MAC layer fairness in wireless packet networks

By T. Nandagopal, Tae-eun Kim, Xia Gao, Vaduvur Bharghavan. 2000

732 citations recorded by the source corpus.

Link-layer fairness models that have been proposed for wireline and packet cellular networks cannot be generalized for shared channel wireless networks because of the unique characteristics of the wireless channel, such as location-dependent contention, inherent conflict between optimizing channel utilization and achieving fairness, and the absence of any centralized control. In this paper, we propose a general analytical framework that captures the unique characteristics of shared wireless channels and allows the modeling of a large class of system-wide fairness models via the specification of per-flow utility functions. We show that system-wide fairness can be achieved without explicit global coordination so long as each node executes a contention resolution algorithm that is designed to optimize its local utility function. We present a general mechanism for translating a given fairness model in our framework into a corresponding contention resolution algorithm. Using this translation, we derive the backoff algorithm for achieving proportional fairness in wireless shared channels, and compare the fairness properties of this algorithm with both the ideal proportional fairness objective, and state-of-the-art backoff-based contention resolution algorithms. We believe that the two aspects of the proposed framework, i.e. the ability to specify arbitrary fairness models via local utility functions, and the ability to automatically generate local contention resolution mechanisms in response to a given utility function, together provide the path for achieving flexible service differentiation in future shared channel wireless networks.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

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Citations in the corpus

Fair Resource Allocation in Federated Learning (2019, background): “, 2008) and wireless communications (Eryilmaz & Srikant, 2006; Nandagopal et al., 2000; Sanjabi et al., 2014; Shi et al., 2014).”
Handbook of Wireless Networks and Mobile Computing (2002, methodology): “In [13], a mutation operator that concentrates on the change of conflicting frequencies was used, whereas in [14] several ways of dealing with the cosite constraints were discussed.”
Layering as Optimization Decomposition: A Mathematical Theory of Network Architectures (2007, methodology): “In [98], [39], [16], a fluid approximation approach is used where each maximum clique is defined as a resource with a finite capacity that is shared by the links belonging to the clique.”
End-to-end performance and fairness in multihop wireless backhaul networks (2004, background): “In the case of CSMA/CA, RTS/CTS exchange results in a decreased number of collisions, however introduces the problem of “information asymmetry” (see [2, 16, 24]), where TAP has no information of transmissions between TAP and TAP .”
Capacity of Ad Hoc wireless networks (2001, background): “[12] propose an algorithm that gives each flow in the network a fair allocatio n of capacity no matter how much more contention it perceives in c omparison to other flows.”
What is the right model for wireless channel interference? (2006, background): “The interference range model assumes fixed ranges for communication and interference (for example, see [11], [16]).”
Modeling Per-Flow Throughput and Capturing Starvation in CSMA Multi-Hop Wireless Networks (2006, methodology): “Several forms of fairness have been proposed: weighted fairness [14], [23], max-min fairness [15], [29] and proportional fairness [18], [22]; these objectives have been implemented either using TDMA or random access.”
Real-time communication and coordination in embedded sensor networks (2003, background): “This is attributed to the following reasons: (1) Fairness of the underlying MAC protocol: It has been shown in [121] that as the widely adopted IEEE 802.”
Wireless sensor networks: a survey (2002, methodology): “The ARC uses a linear increase and multiplicative decrease approach [57].”
A transmission control scheme for media access in sensor networks (2001, background): “Prior work shows that an adaptive rate control algorithm is very effective in achieving proportional fairness of media access for packet radio [16].”
Impact of Interference on Multi-Hop Wireless Network Performance (2003, background): “However, like [23], their conflict graph is also defined on flows rather than links.”
Medium Access Control protocols for ad hoc wireless networks: A survey (2006, background): “[102] have also proposed a general analytical framework for modeling the fairness.”