General Interference Model Research Articles

Distributed throughput-optimal scheduling framework with delay analysis in multi-hop wireless networks

In wireless networks, due to the shared medium, we require sophisticated algorithms to schedule concurrent transmissions that meet the interference constraint where two nodes cannot transmit simultaneously in a guaranteed interference range of each other. For the general ( K -hop) interference model, 1 1 This is the generalization of the interference model where two nodes cannot transmit simultaneously if they are within K-hop neighbors of each other due to the shared wireless medium. especially with K ≥ 2 , the throughput-optimal centralized scheduler needs to solve a NP-Hard problem. It leads to the desire of a distributed, low-complexity but throughput-optimal scheduling algorithm. Inspired by this problem, we generalize a randomized scheduling framework for a K -hop interference model and prove that any scheduling algorithm can achieve the capacity of the system if it satisfies the constraints of this framework. Then, we develop two randomized distributed scheduling algorithms which can be integrated into this framework. In spite of having the constant time-complexity, the first proposed algorithm can lead to the exponential growth of the network delay. The second one is a maximal matching algorithm having better delay performance with polynomial growth of delay in the network size. We also show that the whole time-complexity of this randomized distributed scheduling framework is polynomial in network size with any finite value of K .

A Distributed CSMA Algorithm for Throughput and Utility Maximization in Wireless Networks

In multihop wireless networks, designing distributed scheduling algorithms to achieve the maximal throughput is a challenging problem because of the complex interference constraints among different links. Traditional maximal-weight scheduling (MWS), although throughput-optimal, is difficult to implement in distributed networks. On the other hand, a distributed greedy protocol similar to IEEE 802.11 does not guarantee the maximal throughput. In this paper, we introduce an adaptive carrier sense multiple access (CSMA) scheduling algorithm that can achieve the maximal throughput distributively. Some of the major advantages of the algorithm are that it applies to a very general interference model and that it is simple, distributed, and asynchronous. Furthermore, the algorithm is combined with congestion control to achieve the optimal utility and fairness of competing flows. Simulations verify the effectiveness of the algorithm. Also, the adaptive CSMA scheduling is a modular MAC-layer algorithm that can be combined with various protocols in the transport layer and network layer. Finally, the paper explores some implementation issues in the setting of 802.11 networks.

Joint Routing, Channel Assignment, and Scheduling for Throughput Maximization in General Interference Models

Throughput optimization in wireless networks with multiple channels and multiple radio interfaces per node is a challenging problem. For general traffic models (given a set of source-destination pairs), optimization of throughput entails design of ¿efficient¿ routes between the given source-destination pairs, in conjunction with (1) assignment of channels to interfaces and communication links and (2) scheduling of noninterfering links for simultaneous transmission. Prior work has looked at restricted versions of the above problem. In this paper, we design approximation algorithms for the joint routing, channel assignment, and link scheduling problem in wireless networks with general interference models. The unique contributions of our work include addressing the above joint problem in the context of physical interference model and single-path routing (wherein, traffic between a source-destination pair is restricted to a single path). To the best of our knowledge, ours is the first work to address the throughput maximization problem in such general contexts. For each setting, we design approximation algorithms with provable performance guarantees. We demonstrate the effectiveness of our algorithms in general contexts through simulations.

Control of wireless networks with flow level dynamics under constant time scheduling

We consider a network control problem for wireless networks with flow level dynamics under the general k-hop interference model. In particular, we investigate the control problem in low load and high load regimes. In the low load regime, we show that the network can be stabilized by a regulated maximal scheduling policy considering flow level dynamics if the offered load satisfies a constraining bound condition. Because maximal scheduling is a general scheduling rule whose implementation is not specified, we propose a constant-time and distributed scheduling algorithm for a general k-hop interference model which can approximate the maximal scheduling policy within an arbitrarily small error. Under the stability condition, we show how to calculate transmission rates for different user classes such that the long-term (time average) network utility is maximized. This long-term network utility captures the real network performance due to the fact that under flow level dynamics, the number of users randomly change so instantaneous network utility maximization does not result in useful network performance. Our results imply that congestion control is unnecessary when the offered load is low and optimal user rates can be determined to maximize users’ long-term satisfaction. In the high load regime where the network can be unstable under the regulated maximal scheduling policy, we propose a cross-layer congestion control and scheduling algorithm which can stabilize the network under arbitrary network load. Through extensive numerical analysis for some typical networks, we show that the proposed scheduling algorithm has much lower overhead than other existing queue-length-based constant-time scheduling schemes in the literature, and it achieves performance much better than the guaranteed bound.

Scheduling Efficiency of Distributed Greedy Scheduling Algorithms in Wireless Networks

We consider the problem of distributed scheduling in wireless networks subject to simple collision constraints. We define the efficiency of a distributed scheduling algorithm to be the largest number (fraction) such that the throughput under the distributed scheduling policy is at least equal to the efficiency multiplied by the maximum throughput achievable under a centralized policy. For a general interference model, we prove a lower bound on the efficiency of a distributed scheduling algorithm by first assuming that all of the traffic only uses one hop of the network. We also prove that the lower bound is tight in the sense that, for any fraction larger than the lower bound, we can find a topology and an arrival rate vector within the fraction of the capacity region such that the network is unstable under a greedy scheduling policy. We then extend our results to a more general multihop traffic scenario and show that similar scheduling efficiency results can be established by introducing prioritization or regulators to the basic greedy scheduling algorithm

Maximizing throughput in wireless networks via gossiping

A major challenge in the design of wireless networks is the need for distributed scheduling algorithms that will efficiently share the common spectrum. Recently, a few distributed algorithms for networks in which a node can converse with at most a single neighbor at a time have been presented. These algorithms guarantee 50% of the maximum possible throughput. We present the first distributed scheduling framework that guarantees maximum throughput . It is based on a combination of a distributed matching algorithm and an algorithm that compares and merges successive matching solutions. The comparison can be done by a deterministic algorithm or by randomized gossip algorithms. In the latter case, the comparison may be inaccurate. Yet, we show that if the matching and gossip algorithms satisfy simple conditions related to their performance and to the inaccuracy of the comparison (respectively), the framework attains the desired throughput.It is shown that the complexities of our algorithms, that achieve nearly 100% throughput, are comparable to those of the algorithms that achieve 50% throughput. Finally, we discuss extensions to general interference models. Even for such models, the framework provides a simple distributed throughput optimal algorithm.

The general interference model in the fuzzy reliability analysis of systems

The interference model of the fuzzy reliability analysis has been the focus of some researches. In this paper, the author proposed a general interference model for fuzzy reliability analysis, which based on the safety condition, not use the stress-strength interference model. Therefore, the proposed model can apply for every reliability problems of the systems.

Optimality of type I orthogonal arrays for general interference model with correlated observations

We consider a general interference model which includes as special cases interference models as well as cross-over models. In the paper, we extend the results of Kunert and Martin (J. Statist. Plann. Inference 87 (2000a) 119) showing that orthogonal arrays of type I are universally optimal binary designs not only for cross-over models but also for the general interference model with correlated observations.

Estimation in the presence of interferences

If, in a linear regression model, outliers are present on some components of the observation vector, one uses robust estimation schemes that downweight their influnce. If interferences that perturb the whole observation vector are present, one generally assumes to know the interfering subspace and performs the parameter estimation on its orthogonal complement. A more general interference model is considered. The interferences belong to a known parametrized family that spaus the whole space. The number and the range space of the interferences that are indeed present is unknown and a robust estimation scheme selects the interferences that are present and downweights their influence,

Foveal Load Affects the Functional Field of View

The results of three tachistoscopic experiments are reported, which suggest that the functional or useful field of view is very sensitive to foveal demands (load). As the foveal primary task becomes more difficult, peripheral information extraction is perturbed, and it is perturbed increasingly as the retinal eccentricity of the peripheral information increases. This is the case even when compensatory adjustments are made for acuity loss. The results are discussed in terms of tunnel vision and general interference models.