Towards Identifying Performance Anomalies

AbstractLarge-scale-software systems (LSSs) are composed of hundreds of subsystems that interact with each other in an unforeseen and complex ways. The operators of these LSSs strictly monitor thousands of metrics (performance counters) to quickly identify performance anomalies before a catastrophe. The existing monitoring tools and methodologies have not kept in pace with the rapid growth and inherit complexity of these LSSs; hence are ineffective in assisting practitioners to effectively pinpoint performance anomalies. We propose a methodology that uses entropy analysis to assist practitioners/operators of LSSs in quickly detecting underlying anomalies in the system. Our performance tests conducted on an open source benchmark system reveal that the proposed methodology is robust in pinpointing anomalies, do not require any domain knowledge to operate, and avoid information overload on practitioners

An Adaptive User Interface in Healthcare

AbstractHealthcare is a broad subject with many different challenges, yet it is important and relatable to everyone. The aging Baby Boomer generation is an important healthcare issue today. In Canada, and many other developed nations, the number of citizens reaching the age of retirement and seniority is growing faster than the rate of citizens working and providing health related services. As people age they tend to require more frequent checkups and health services, ultimately putting a bigger resource drain on healthcare infrastructure. New advancements in Computer Science and Engineering are allowing the development of next generation applications with the purpose of providing healthcare services in a cost effective and efficient way. This paper proposes a multi-agent system for tracking and monitoring health data for patients. Furthermore, agents within the system use reinforcement learning techniques to build an adaptive user interface for each human user. The actions and behaviour of users are monitored and used to modify their respective user interface over time. To demonstrate the feasibility of the architecture, two scenarios are provided. We conclude with several possible future directions for this research

Dynamic Healthcare Interface for Patients

AbstractCanadian healthcare is a fundamental part of society. Challenges such as the aging baby boomer generation require the healthcare industry to meet higher demands while using fewer resources. Computer systems designed to record and report physical health properties of an individual personcan be used in part to accomplish this task. In this paper, we present the architecture of a hypothetical multi-agent system designed to provide healthcare information about specific patients through continuous monitoring. The resulting data from the system is accessible by the patient to whom it belongs as well as his or her healthcare professional. Furthermore, the proposed system utilizes an adaptive user interface for the purpose of improving the overall experience for users with poor vision or motor skills. Specifically, we focus on the implementation of several of the key components involved in the adaptive user interface: learning component and the user model. To demonstrate the feasibility of the implementation two scenarios are provided. We conclude with several possible future directions for this research

Comparative Study of Fingerprint and Centroid Localization Protocol Using COOJA

AbstractSensor networks are in a numerous number of applications. However, implementing wireless sensor networks present new challenges compared with theoretical networks. Cooja is the Contiki network simulator. It allows large and small networks of Contiki motes to be simulated; moreover, motes can be emulated at the hardware level. In this paper, we evaluate the accuracy performance of two very well-known localization protocols, namely: fingerprint and centroid protocols using Tmote sky in Cooja. It is worth mentioning that this the first time this study is conducted in Cooja. The results conform to the theory that fingerprint protocol has a better performance than centroid in terms of accuracy when accuracy is quantified

Integrated Context-Aware Driver Assistance System Architecture

Recently, significant improvements have been made in the area of vehicular communication systems. Furthermore, vehicle-to-vehicle communication is considered a key concept for keeping roads safe. An efficient implementation of these systems is necessary to ensure the safety of driving situations and to reduce the collision rates. This paper proposes a Context-Aware Driver Assistance System that links drivers with the physical environment surrounding them using multiple types of sensors and traffic systems as well as considering the senior driver's difficulties and the system processing time. This is achieved by developing a warning system that assists drivers to avoid collisions and improve their response times. The proposed system architecture consists of a set of components to process the user's request such as parking assistance, and to provide responses and advices when needed. These components include communication, knowledge exchange, knowledge update, and context-history. Also, it includes other processes such as context-history manipulation, hazard detection, and hazard detection control. The main goal of the proposed system is to reduce the number of car accidents and improve driver's decisions. The NXT Robotic environment is used to demonstrate the feasibility of the proposed system

Fault Reconnaissance Agent for Sensor Networks

One of the key prerequisite for a scalable, effective and efficient sensor network is the utilization of low-cost, low-overhead and high-resilient fault-inference techniques. To this end, we propose an intelligent agent system with a problem solving capability to address the issue of fault inference in sensor network environments. The intelligent agent system is designed and implemented at base-station side. The core of the agent system – problem solver – implements a fault-detection inference engine which harnesses Expectation Maximization (EM) algorithm to estimate fault probabilities of sensor nodes. To validate the correctness and effectiveness of the intelligent agent system, a set of experiments in a wireless sensor testbed are conducted. The experimental results show that our intelligent agent system is able to precisely estimate the fault probability of sensor nodes

A Web-Based Application of TELOSB Sensor Network

Sensor network can be used in a numerous number of applications. However, implementing wireless sensor networks present new challenges compared with theoretical networks. In addition, implementing a sensor network might provide results different from that derived theoretically. Some routing protocols when implemented might fail to perform. In this paper, we implement three routing protocols, namely: Dynamic MANET on-demand, Collection Tree and Dissemination protocols. To compare the performance of these protocols, they are implemented using a Telosb sensor network. Several performance metrics are carried out to demonstrate the pros and cons of these protocols. A telemedicine application is tested in top of the implemented Telosb sensor network at King Fahd University of Petroleum and Minerals Clinic in Saudi Arabia, utilizing Alive ECG sensors