A dag-based algorithm for distributed mutual exclusion

Call number: LD2668 .T4 CMSC 1989 N45Master of ScienceComputing and Information Science

An efficient distributed mutual exclusion algorithm based on relative consensus voting

2003-2004 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Synthesizing Finite-state Protocols from Scenarios and Requirements

Scenarios, or Message Sequence Charts, offer an intuitive way of describing the desired behaviors of a distributed protocol. In this paper we propose a new way of specifying finite-state protocols using scenarios: we show that it is possible to automatically derive a distributed implementation from a set of scenarios augmented with a set of safety and liveness requirements, provided the given scenarios adequately \emph{cover} all the states of the desired implementation. We first derive incomplete state machines from the given scenarios, and then synthesis corresponds to completing the transition relation of individual processes so that the global product meets the specified requirements. This completion problem, in general, has the same complexity, PSPACE, as the verification problem, but unlike the verification problem, is NP-complete for a constant number of processes. We present two algorithms for solving the completion problem, one based on a heuristic search in the space of possible completions and one based on OBDD-based symbolic fixpoint computation. We evaluate the proposed methodology for protocol specification and the effectiveness of the synthesis algorithms using the classical alternating-bit protocol.Comment: This is the working draft of a paper currently in submission. (February 10, 2014

Graphical Simulation Tool from Logical Token-based Distributed Mutual Exclusion Algorithms�

Computer Science

Distributed mutual exclusion algorithms

In this thesis we present three original algorithms which solve the distributed mutual exclusion problem. Two of the three solve the problem of allowing only one site at a time into the critical section. The third solves the more difficult problem of allowing a specific number of sites (k sites) into the critical section at a time; All three algorithms are Token Based . That is, they make use of a token and token queue in order to guarantee mutual exclusion. Only the site that currently has the token is allowed to enter its critical section in the 1 mutual exclusion algorithms. Only the sites that have seen the token, since they requested it, are allowed to enter their critical sections in the k mutual exclusion algorithm; The primary goal of our algorithms is efficiency. Both of our 1 mutual exclusion algorithms require between 2 and n messages per critical section (n being the number of sites) depending on the number of requests for the critical section. Our k mutual exclusion has similar requirements between 3 and n messages per critical section depending on the number of requests for the critical section. (Abstract shortened by UMI.)

Logical rings in the mutual exclusion problem of distributed memory systems

In this thesis, we investigate distributed mutual exclusion algorithms and delineate the features of a new distributed mutual exclusion algorithm. The basis of the algorithm is the logical ring structure employed in token-based mutual exclusion algorithms. Specifically, there exists dynamic properties of the logical ring that, given certain restrictions regarding message traffic flow, passively give useful information about the location of the token. Effectively, the algorithm demonstrates a type of intelligent routing that identifies useful shortcuts to in the routing of the token. The result is a reduction in the total number of messages exchanged prior to the execution of the critical section as compared to the algorithm proposed by Fu and Tzeng (7). Furthermore, the algorithm allows for an increased degree of fairness in a lightly loaded system than that allowed by Fu and Tzeng\u27s algorithm

Classification of the Structural Behavior of Tall Buildings with a Diagrid Structure: A Machine Learning-Based Approach

We study the relationship between the architectural form of tall buildings and their structural response to a conventional seismic load. A series of models are generated by varying the top and bottom plan geometries of the buildings, and a steel diagrid structure is mapped onto their skin. A supervised machine learning approach is then adopted to learn the features of the aforementioned relationship. Six different classifiers, namely k-nearest neighbour, support vector machine, decision tree, ensemble method, discriminant analysis, and naive Bayes, are adopted to this aim, targeting the structural response as the building drift, i.e., the lateral displacement at its top under the considered external excitation. By focusing on the classification of the structural response, it is shown that some classifiers, like, e.g., decision tree, k-nearest neighbour and the ensemble method, can learn well the structural behavior, and can therefore help design teams to select more efficient structural solutions

Traffic-Driven Energy Efficient Operational Mechanisms in Cellular Access Networks

Recent explosive growth in mobile data traffic is increasing energy consumption in cellular networks at an incredible rate. Moreover, as a direct result of the conventional static network provisioning approach, a significant amount of electrical energy is being wasted in the existing networks. Therefore, in recent time, the issue of designing energy efficient cellular networks has drawn significant attention, which is also the foremost motivation behind this research. The proposed research is particularly focused on the design of self-organizing type traffic-sensitive dynamic network reconfiguring mechanisms for energy efficiency in cellular systems. Under the proposed techniques, radio access networks (RANs) are adaptively reconfigured using less equipment leading to reduced energy utilization. Several energy efficient cellular network frameworks by employing inter-base station (BS) cooperation in RANs are proposed. Under these frameworks, based on the instantaneous traffic demand, BSs are dynamically switched between active and sleep modes by redistributing traffic among them and thus, energy savings is achieved. The focus is then extended to exploiting the availability of multiple cellular networks for extracting energy savings through inter-RAN cooperation. Mathematical models for both of these single-RAN and multi-RAN cooperation mechanisms are also formulated. An alternative energy saving technique using dynamic sectorization (DS) under which some of the sectors in the underutilized BSs are turned into sleep mode is also proposed. Algorithms for both the distributed and the centralized implementations are developed. Finally, a two-dimensional energy efficient network provisioning mechanism is proposed by jointly applying both the DS and the dynamic BS switching. Extensive simulations are carried out, which demonstrate the capability of the proposed mechanisms in substantially enhancing the energy efficiency of cellular networks