Stable routing scheduling algorithms in multi-hop wireless networks

Stability is an important issue in order to characterize the performance of a network, and it has become a major topic of study in the last decade. Roughly speaking, a communication network system is said to be stableif the number of packets waiting to be delivered (backlog) is finitely bounded at any one time. In this paper we introduce a number of routing scheduling algorithms which, making use of certain knowledge about the network’s structure, guarantee stability for certain injection rates. First, we introduce two new families of combinatorial structures, which we call universally strong selectorsand generalized universally strong selectors, that are used to provide a set of transmission schedules. Making use of these structures, we propose two local-knowledgepacket-oblivious routing scheduling algorithms. The first proposed routing scheduling algorithm onlyneeds to know some upper bounds on the number of links and on the network’s degree, and is asymptotically optimal regarding the injection rate for which stability is guaranteed. The second proposed routing scheduling algorithm isclose to be asymptotically optimal, but it only needs to know an upper bound on the number of links. For such algorithms, we also provide some results regarding both the maximum latencies and queue lengths. Furthermore, we also evaluate how the lack of global knowledge about the system topology affects the performance of the routing scheduling algorithms.Funding for open access charge: CRUE-Universitat Jaume

The robustness of stability under link and node failures

AbstractIn the area of communication systems, stability refers to the property of keeping the amount of traffic in the system always bounded over time. Different communication system models have been proposed in order to capture the unpredictable behavior of some users and applications. Among those proposed models the adversarial queueing theory (aqt) model turned out to be the most adequate to analyze an unpredictable network. Until now, most of the research done in this field did not consider the possibility of the adversary producing failures on the network structure. The adversarial models proposed in this work incorporate the possibility of dealing with node and link failures provoked by the adversary. Such failures produce temporal disruptions of the connectivity of the system and increase the collisions of packets in the intermediate hosts of the network, and thus the average traffic load. Under such a scenario, the network is required to be equipped with some mechanism for dealing with those collisions.In addition to proposing adversarial models for faulty systems we study the relation between the robustness of the stability of the system and the management of the queues affected by the failures. When the adversary produces link or node failures the queues associated to the corresponding links can be affected in many different ways depending on whether they can receive or serve packets, or rather that they cannot. In most of the cases, protocols and networks containing very simple topologies, which were known to be universally stable in the aqt model, turn out to be unstable under some of the newly proposed adversarial models. This shows that universal stability of networks is not a robust property in the presence of failures

Adversarial models for priority-based networks

We propose several variations of the adversarial queueing model. The priority model takes into account the case in which the packets can have different priorities, assigned by the adversary at injection time. The variable priority model is an extension of the priority model in which the adversary may change the priority of packets at each time step. The failure and reliable models are designed to cope with dynamic networks in which the adversary controls, under different constraints, the edge failures. We address stability issues in the proposed adversarial models. We show that the set of universally stable networks in the adversarial model remains the same in the priority, variable priority, failure and reliable models. From the point of view of queueing policies we show that several queueing policies that are universally stable in the adversarial model remain so in the priority, failure and reliable models. However, we show that LIS, a universally stable queueing policy in the adversarial model, is not universally stable in any of the other models. Moreover, we show that no greedy queueing policy is universally stable in the variable priority model. Finally we analyze the problem of deciding stability of a given network under a fixed protocol. We provide a characterization of the networks that are stable under FIFO and LIS in the failure model (and therefore in the reliable and priority models). This characterization allows us to show that the stability problem under FIFO and LIS in the failure model can be solved in polynomial time.Postprint (published version

Adversarial models for priority-based networks

We propose several variations of the adversarial queueing model. The priority model takes into account the case in which the packets can have different priorities, assigned by the adversary at injection time. The variable priority model is an extension of the priority model in which the adversary may change the priority of packets at each time step. The failure and reliable models are designed to cope with dynamic networks in which the adversary controls, under different constraints, the edge failures. We address stability issues in the proposed adversarial models. We show that the set of universally stable networks in the adversarial model remains the same in the priority, variable priority, failure and reliable models. From the point of view of queueing policies we show that several queueing policies that are universally stable in the adversarial model remain so in the priority, failure and reliable models. However, we show that LIS, a universally stable queueing policy in the adversarial model, is not universally stable in any of the other models. Moreover, we show that no greedy queueing policy is universally stable in the variable priority model. Finally we analyze the problem of deciding stability of a given network under a fixed protocol. We provide a characterization of the networks that are stable under FIFO and LIS in the failure model (and therefore in the reliable and priority models). This characterization allows us to show that the stability problem under FIFO and LIS in the failure model can be solved in polynomial time

Adversarial models for priority-based networks

In this article, we propose several variations of the adversarial queueing model and address stability issues of networks and protocols in those proposed models. The first such variation is the priority model, which is directed at static network topologies and takes into account the case in which packets can have different priorities. Those priorities are assigned by an adversary at injection time. A second variation, the variable priority model, is an extension of the priority model in which the adversary may dynamically change the priority of packets at each time step. Two more variations, namely the failure model and the reliable model, are proposed to cope with dynamic networks. In the failure and reliable models the adversary controls, under different constraints, the failures that the links of the topology migh