Local Queuing Under Contention

We study stability of local packet scheduling policies in a distributed system of n nodes. The local policies at nodes may only access their local queues, and have no other feedback from the underlying distributed system. The packets arrive at queues according to arrival patterns controlled by an adversary restricted only by injection rate rho and burstiness b. In this work, we assume that the underlying distributed system is a shared channel, in which in order to get rid of a packet from the queue, a node needs to schedule it for transmission on the channel and no other packet is scheduled for transmission at the same time. We show that there is a local adaptive scheduling policy with relatively small memory, which is universally stable on a shared channel, that is, it has bounded queues for any rho= 0. On the other hand, without memory the maximal stable injection rate is O(1/log n). We show a local memoryless (non-adaptive) scheduling policy based on novel idea of ultra strong selectors which is stable for slightly smaller injection c/log^2 n, for some constant c>0

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

Routing in Wireless Networks With Interferences

We consider dynamic routing in multi-hop wireless networks with adversarial traffic. The model of wireless communication incorporates interferences caused by packets' arrivals into the same node that overlap in time. We consider two classes of adversaries: balanced and unbalanced. We demonstrate that, for each routing algorithm and an unbalanced adversary, the algorithm is unstable against this adversary in some networks. We develop a routing algorithm that has bounded packet latency against each balanced adversary

Routing in Wireless Networks With Interferences

We consider dynamic routing in multi-hop wireless networks with adversarial traffic. The model of wireless commu- nication incorporates interferences caused by packets’ arrivals into the same node that overlap in time. We consider two classes of adversaries: balanced and unbalanced. We demonstrate that, for each routing algorithm and an unbalanced adversary, the algorithm is unstable against this adversary in some networks. We develop a routing algorithm that has bounded packet latency against each balanced adversary

Lightweight Robust Framework for Workload Scheduling in Clouds

Reliability, security and stability of cloud services without sacrificing too much resources have become a desired feature in the area of workload management in clouds. The paper proposes and evaluates a lightweight framework for scheduling a workload which part could be unreliable. This unreliability could be caused by various types of failures or attacks. Our framework for robust workload scheduling efficiently combines classic fault-tolerant and security tools, such as packet/job scanning, with workload scheduling, and it does not use any heavy resource-consuming tools, e.g., cryptography or non-linear optimization. More specifically, the framework uses a novel objective function to allocate jobs to servers and constantly decides which job to scan based on a formula associated with the objective function. We show how to set up the objective function and the corresponding scanning procedure to make the system provably stable, provided it satisfies a specific stability condition. As a result, we show that our framework assures cloud stability even if naive scanning-all and scanning-none strategies are not stable. We extend the framework to decentralized scheduling and evaluate it under several popular routing procedures