An Automated Cloud-based Big Data Analytics Platform for Customer Insights

Product reviews have a significant influence on strategic decisions for both businesses and customers on what to produce or buy. However, with the availability of large amounts of online information, manual analysis of reviews is costly and time consuming, as well as being subjective and prone to error. In this work, we present an automated scalable cloud-based system to harness big customer reviews on products for gaining customer insights through data pipeline from data acquisition, analysis to visualisation in an efficient way. The experimental evaluation has shown that the proposed system achieves good performance in terms of accuracy and computing time

Optimized Execution of Deterministic Blocks in Java PathFinder

Java PathFinder (JPF) is an explicit-state model checker for Java programs. It explores all executions that a given program can have due to different thread interleavings and nondeterministic choices. JPF implements a backtracking Java Virtual Machine (JVM) that executes bytecodes using a special representation of JVM states. This special representation enables JPF to quickly store, restore, and compare states; it is crucial for making the overall state exploration efficient. However, this special representation creates overhead for each execution, even execution of deterministic blocks that have no thread interleavings or nondeterministic choices. We propose mixed execution, a technique that improves execution time of deterministic blocks in JPF. Our technique leverages the fact that JPF is written in Java: JPF is a special JVM that runs on top of a regular, host JVM. Mixed execution works by translating the state between the special JPF representation and the host JVM representation. We also present lazy translation, an optimization that speeds up mixed execution by translating only the parts of the state that an execution dynamically depends on. We evaluate mixed execution on six subject programs that use JPF for generating tests for data structures and on one case study for verifying a network protocol. The experimental results show that mixed execution can improve the overall state exploration time up to 36.98%, while improving the execution time of deterministic blocks up to 69.15%

High performance, low complexity cooperative caching for Wireless Sensor Networks

During the last decade, Wireless Sensor Networks (WSNs) have emerged and matured at such point that currently support several applications like environment control, intelligent buildings, target tracking in battlefields, and many more. The vast majority of these applications require an optimization to the communication among the sensors so as to serve data in short latency and with minimal energy consumption. Cooperative data caching has been proposed as an effective and efficient technique to achieve these goals concurrently. The essence of these protocols is the selection of the sensor nodes which will take special roles in running the caching and request forwarding decisions. This article introduces a new metric to aid in the selection of such nodes. Based on this metric, we propose a new cooperative caching protocol, which is compared against the state-of-the-art competing protocols. The simulation results attest the superiority of the proposed protocol; the proposed solution achieves on the average 20% improvement w.r.t. the competing method for the examined performance measures. © 2009 IEEE

An Automated Cloud-Based Big Data Analytics Platform for Customer Insights

Product reviews have a significant influence on strategic decisions for both businesses and customers on what to produce or buy. However, with the availability of large amounts of online information, manual analysis of reviews is costly and time consuming, as well as being subjective and prone to error. In this work, we present an automated scalable cloud-based system to harness big customer reviews on products for gaining customer insights through data pipeline from data acquisition, analysis to visualisation in an efficient way. The experimental evaluation has shown that the proposed system achieves good performance in terms of accuracy and computing time