Enhancing performance and expressibility of complex event processing using binary tree-based directed graph

In various domains, applications are required to detect and react to complex situations accordingly. In response to the demand for matching receiving events to complex patterns, several event processing systems have been developed. However, there are just a few of them considered both performance and expressibility of event matching as focusing only on performance can cause negative effect on the expressibility or vice versa. This research develops a fast adaptive event matching system (FAEM), a new event matching system to improve expressibility and performance measures (throughput and end-to-end latency). This system is designed and developed based on a novel binary tree-based directed graph (BTDG) as a unified basis for event-matching. The proposed system transforms a user-defined query into a set of system objects including buffers, conditions on buffers, cursors, and join operators (non-kleene and kleene operators) and arranges these objects on a BTDG. Provided BTDG the enhancement in performance of non-kleene operators applied through developing a batch removal method to remove the events that are located out of time-window, and an actual time window (ATW) which can improve performance of event matching. To improve performance of kleene operators, this research introduces a twin algorithms for kleene operator which is match to BTDG. These two kleene algorithms apply grouping on events and reduce the number of intermediate results and apply combination algorithm in final stage. Transformation of queries containing join operators into BTDG enhances the expressibility of the proposed CEP system

Design and implementation of a multi-agent opportunistic grid computing platform

Opportunistic Grid Computing involves joining idle computing resources in enterprises into a converged high performance commodity infrastructure. The research described in this dissertation investigates the viability of public resource computing in offering a plethora of possibilities through seamless access to shared compute and storage resources. The research proposes and conceptualizes the Multi-Agent Opportunistic Grid (MAOG) solution in an Information and Communication Technologies for Development (ICT4D) initiative to address some limitations prevalent in traditional distributed system implementations. Proof-of-concept software components based on JADE (Java Agent Development Framework) validated Multi-Agent Systems (MAS) as an important tool for provisioning of Opportunistic Grid Computing platforms. Exploration of agent technologies within the research context identified two key components which improve access to extended computer capabilities. The first component is a Mobile Agent (MA) compute component in which a group of agents interact to pool shared processor cycles. The compute component integrates dynamic resource identification and allocation strategies by incorporating the Contract Net Protocol (CNP) and rule based reasoning concepts. The second service is a MAS based storage component realized through disk mirroring and Google file-system’s chunking with atomic append storage techniques. This research provides a candidate Opportunistic Grid Computing platform design and implementation through the use of MAS. Experiments conducted validated the design and implementation of the compute and storage services. From results, support for processing user applications; resource identification and allocation; and rule based reasoning validated the MA compute component. A MAS based file-system that implements chunking optimizations was considered to be optimum based on evaluations. The findings from the undertaken experiments also validated the functional adequacy of the implementation, and show the suitability of MAS for provisioning of robust, autonomous, and intelligent platforms. The context of this research, ICT4D, provides a solution to optimizing and increasing the utilization of computing resources that are usually idle in these contexts

Design and implementation of a multi-agent opportunistic grid computing platform

Opportunistic Grid Computing involves joining idle computing resources in enterprises into a converged high performance commodity infrastructure. The research described in this dissertation investigates the viability of public resource computing in offering a plethora of possibilities through seamless access to shared compute and storage resources. The research proposes and conceptualizes the Multi-Agent Opportunistic Grid (MAOG) solution in an Information and Communication Technologies for Development (ICT4D) initiative to address some limitations prevalent in traditional distributed system implementations. Proof-of-concept software components based on JADE (Java Agent Development Framework) validated Multi-Agent Systems (MAS) as an important tool for provisioning of Opportunistic Grid Computing platforms. Exploration of agent technologies within the research context identified two key components which improve access to extended computer capabilities. The first component is a Mobile Agent (MA) compute component in which a group of agents interact to pool shared processor cycles. The compute component integrates dynamic resource identification and allocation strategies by incorporating the Contract Net Protocol (CNP) and rule based reasoning concepts. The second service is a MAS based storage component realized through disk mirroring and Google file-system’s chunking with atomic append storage techniques. This research provides a candidate Opportunistic Grid Computing platform design and implementation through the use of MAS. Experiments conducted validated the design and implementation of the compute and storage services. From results, support for processing user applications; resource identification and allocation; and rule based reasoning validated the MA compute component. A MAS based file-system that implements chunking optimizations was considered to be optimum based on evaluations. The findings from the undertaken experiments also validated the functional adequacy of the implementation, and show the suitability of MAS for provisioning of robust, autonomous, and intelligent platforms. The context of this research, ICT4D, provides a solution to optimizing and increasing the utilization of computing resources that are usually idle in these contexts