Kahn Process Networks and a Reactive Extension

Kahn and MacQueen have introduced a generic class of determinate asynchronous data-flow applications, called Kahn Process Networks (KPNs) with an elegant mathematical model and semantics in terms of Scott-continuous functions on data streams together with an implementation model of independent asynchronous sequential programs communicating through FIFO buffers with blocking read and non-blocking write operations. The two are related by the Kahn Principle which states that a realization according to the implementation model behaves as predicted by the mathematical function. Additional steps are required to arrive at an actual implementation of a KPN to take care of scheduling of independent processes on a single processor and to manage communication buffers. Because of the expressiveness of the KPN model, buffer sizes and schedules cannot be determined at design time in general and require dynamic run-time system support. Constraints are discussed that need to be placed on such system support so as to maintain the Kahn Principle.We then discuss a possible extension of the KPN model to include the possibility for sporadic, reactive behavior which is not possible in the standard model. The extended model is called Reactive Process Networks. We introduce its semantics, look at analyzability and at more constrained data-flow models combined with reactive behavior

Causal synchrony in the design of distributed programs

The outcome of any computation is determined by the order of the events in the computation and the state of the component variables of the computation at those events. The level of knowledge that can be obtained about event order and process state influences protocol design and operation. In a centralized system, the presence of a physical clock makes it easy to determine event order. It is a more difficult task in a distributed system because there is normally no global time. Hence, there is no common time reference to be used for ordering events. as a consequence, distributed protocols are often designed without explicit reference to event order. Instead they are based on some approximation of global state. Because global state is also difficult to identify in a distributed system, the resulting protocols are not as efficient or clear as they could be.;We subscribe to Lamport\u27s proposition that the relevant temporal ordering of any two events is determined by their causal relationship and that knowledge of the causal order can be a powerful tool in protocol design. Mattern\u27s vector time can be used to identify the causal order, thereby providing the common frame of reference needed to order events in a distributed computation. In this dissertation we present a consistent methodology for analysis and design of distributed protocols that is based on the causal order and vector time. Using it we can specify conditions which must be met for a protocol to be correct, we can define the axiomatic protocol specifications, and we can structure reasoning about the correctness of the specified protocol. Employing causality as a unifying concept clarifies protocol specifications and correctness arguments because it enables them to be defined purely in terms of local states and local events.;We have successfully applied this methodology to the problems of distributed termination detection, distributed deadlock detection and resolution, and optimistic recovery. In all cases, the causally synchronous protocols we have presented are efficient and demonstrably correct

A distribute deadlock detection and resolution algorithm using agents

Deadlock is an intrinsic bottleneck in Distributed Real-Time Database Systems (DRTDBS). Deadlock detection and resolution algorithms are important because in DRTDBS, deadlocked transactions are prone to missing deadlines. We propose an Agent Deadlock Detection and Resolution algorithm (ADCombine), a novel framework for distributed deadlock handling using stationary agents, to address the high overhead suffered by current agent-based algorithms. We test a combined deadlock detection and resolution algorithm that enables the Multi Agent System to adjust its execution based on the changing system load, and that selects its victim transactions more judiciously. We demonstrate the advantages of ADCombine over existing algorithms that use agents or traditional edge-chasing through simulation experiments that measure overhead and performance under a widely varying of experimental conditions.deadlockdistribute real-time database systemsdrtdbsalgorithmmulti agent syste

Resource Management in Multi-Access Edge Computing (MEC)

This PhD thesis investigates the effective ways of managing the resources of a Multi-Access Edge Computing Platform (MEC) in 5th Generation Mobile Communication (5G) networks. The main characteristics of MEC include distributed nature, proximity to users, and high availability. Based on these key features, solutions have been proposed for effective resource management. In this research, two aspects of resource management in MEC have been addressed. They are the computational resource and the caching resource which corresponds to the services provided by the MEC. MEC is a new 5G enabling technology proposed to reduce latency by bringing cloud computing capability closer to end-user Internet of Things (IoT) and mobile devices. MEC would support latency-critical user applications such as driverless cars and e-health. These applications will depend on resources and services provided by the MEC. However, MEC has limited computational and storage resources compared to the cloud. Therefore, it is important to ensure a reliable MEC network communication during resource provisioning by eradicating the chances of deadlock. Deadlock may occur due to a huge number of devices contending for a limited amount of resources if adequate measures are not put in place. It is crucial to eradicate deadlock while scheduling and provisioning resources on MEC to achieve a highly reliable and readily available system to support latency-critical applications. In this research, a deadlock avoidance resource provisioning algorithm has been proposed for industrial IoT devices using MEC platforms to ensure higher reliability of network interactions. The proposed scheme incorporates Banker’s resource-request algorithm using Software Defined Networking (SDN) to reduce communication overhead. Simulation and experimental results have shown that system deadlock can be prevented by applying the proposed algorithm which ultimately leads to a more reliable network interaction between mobile stations and MEC platforms. Additionally, this research explores the use of MEC as a caching platform as it is proclaimed as a key technology for reducing service processing delays in 5G networks. Caching on MEC decreases service latency and improve data content access by allowing direct content delivery through the edge without fetching data from the remote server. Caching on MEC is also deemed as an effective approach that guarantees more reachability due to proximity to endusers. In this regard, a novel hybrid content caching algorithm has been proposed for MEC platforms to increase their caching efficiency. The proposed algorithm is a unification of a modified Belady’s algorithm and a distributed cooperative caching algorithm to improve data access while reducing latency. A polynomial fit algorithm with Lagrange interpolation is employed to predict future request references for Belady’s algorithm. Experimental results show that the proposed algorithm obtains 4% more cache hits due to its selective caching approach when compared with case study algorithms. Results also show that the use of a cooperative algorithm can improve the total cache hits up to 80%. Furthermore, this thesis has also explored another predictive caching scheme to further improve caching efficiency. The motivation was to investigate another predictive caching approach as an improvement to the formal. A Predictive Collaborative Replacement (PCR) caching framework has been proposed as a result which consists of three schemes. Each of the schemes addresses a particular problem. The proactive predictive scheme has been proposed to address the problem of continuous change in cache popularity trends. The collaborative scheme addresses the problem of cache redundancy in the collaborative space. Finally, the replacement scheme is a solution to evict cold cache blocks and increase hit ratio. Simulation experiment has shown that the replacement scheme achieves 3% more cache hits than existing replacement algorithms such as Least Recently Used, Multi Queue and Frequency-based replacement. PCR algorithm has been tested using a real dataset (MovieLens20M dataset) and compared with an existing contemporary predictive algorithm. Results show that PCR performs better with a 25% increase in hit ratio and a 10% CPU utilization overhead

An adaptive load sensing priority assignment protocol for distributed real-time database systems.

Transaction processing in a distributed real time database system (DRTDBS) is coordinated by a concurrency control protocol (CCP). The performance of a CCP is affected by the load condition of a transaction processing system. For example, the performance of the Adaptive Speculative Locking (ASL) protocol degrades in high load conditions of the system. Priority protocols help a CCP by prioritizing transactions. The performance of the priority protocols is also affected by system load conditions, but they can be optimized by dynamically switching between priority protocols at run time when the system load changes. The objective of this research is to develop a protocol, Adaptive Priority Assignment protocol (APAP), which changes the priority protocol at run time to improve the performance of a CCP in a DRTDBS. APAP is implemented in a DRTDBS, where ASL is used as the underlying CCP to validate APAP. The performance of APAP was tested under varying system load conditions with various combinations of the database system parameters. Under the scenarios tested, APAP performed better than other priority protocols and demonstrated that dynamic selection of priority protocols during run time is an effective way to improve the performance of a CCP in a DRTDBS. --Leaf ii.The original print copy of this thesis may be available here: http://wizard.unbc.ca/record=b183575

An Introduction to Database Systems

This textbook introduces the basic concepts of database systems. These concepts are presented through numerous examples in modeling and design. The material in this book is geared to an introductory course in database systems offered at the junior or senior level of Computer Science. It could also be used in a first year graduate course in database systems, focusing on a selection of the advanced topics in the latter chapters