Virtual Laboratories in Cloud Infrastructure of Educational Institutions

Modern educational institutions widely used virtual laboratories and cloud technologies. In practice must deal with security, processing speed and other tasks. The paper describes the experience of the construction of an experimental stand cloud computing and network management. Models and control principles set forth herein.Comment: 3 pages, Published in: 2014 2nd International Conference on Emission Electronics (ICEE), Saint-Petersburg, Russi

Performance Analysis of Transactional Traffic in Mobile Ad-hoc Networks

Mobile Ad Hoc networks (MANETs) present unique challenge to new protocol design, especially in scenarios where nodes are highly mobile. Routing protocols performance is essential to the performance of wireless networks especially in mobile ad-hoc scenarios. The development of new routing protocols requires com- paring them against well-known protocols in various simulation environments. The protocols should be analysed under realistic conditions including, but not limited to, representative data transmission models, limited buffer space for data transmission, sensible simulation area and transmission range combination, and realistic moving patterns of the mobiles nodes. Furthermore, application traffic like transactional application traffic has not been investigated for domain-specific MANETs scenarios. Overall, there are not enough performance comparison work in the past literatures. This thesis presents extensive performance comparison among MANETs comparing transactional traffic including both highly-dynamic environment as well as low-mobility cases

Node Caching Enhancement of Reactive Ad Hoc Routing Protocol

Enhancing route request broadcasting protocols constitutes a substantial part of research in mobile ad hoc network routing. In the thesis, enhancements of ad hoc routing protocols, energy efficiency metrics and clustered topology generators are discussed. The contributions include the followings. First, a node caching enhancement of Ad-hoc On-demand Distance Vector (AODV) routing protocol is introduced. Extensive simulation studies of the enhanced AODV in NS2 shows up to 9-fold reduction in the routing overhead, up to 20% improvement in the packet delivery ratio and up to 60% reduction in the end-to-end delay. The largest improvement happens to highly stressed situations. Secondly, new metrics for evaluating energy efficiency of routing protocols are suggested. New node cached AODV protocols employing non-adaptive and adaptive load balancing techniques were proposed for extending network lifetime and increasing network throughput. Finally, the impact of node clustered topology on ad hoc network is explored. A novel method for generating clustered layout in NS2 is introduced and experiments indicate performance degradation of AODV protocols for the case of two clusters

Optimal resource allocation algorithms for cloud computing

Cloud computing is emerging as an important platform for business, personal and mobile computing applications. We consider a stochastic model of a cloud computing cluster, where jobs arrive according to a random process and request virtual machines (VMs), which are specified in terms of resources such as CPU, memory and storage space. The jobs are first routed to one of the servers when they arrive and are queued at the servers. Each server then chooses a set of jobs from its queues so that it has enough resources to serve all of them simultaneously. There are many design issues associated with such systems. One important issue is the resource allocation problem, i.e., the design of algorithms for load balancing among servers, and algorithms for scheduling VM configurations. Given our model of a cloud, we define its capacity, i.e., the maximum rates at which jobs can be processed in such a system. An algorithm is said to be throughput-optimal if it can stabilize the system whenever the load is within the capacity region. We show that the widely-used Best-Fit scheduling algorithm is not throughput-optimal. We first consider the problem where the jobs need to be scheduled nonpreemptively on servers. Under the assumptions that the job sizes are known and bounded, we present algorithms that achieve any arbitrary fraction of the capacity region of the cloud. We then relax these assumptions and present a load balancing and scheduling algorithm that is throughput optimal when job sizes are unknown. In this case, job sizes (durations) are modeled as random variables with possibly unbounded support. Delay is a more important metric then throughput optimality in practice. However, analysis of delay of resource allocation algorithms is difficult, so we study the system in the asymptotic limit as the load approaches the boundary of the capacity region. This limit is called the heavy traffic regime. Assuming that the jobs can be preempted once after several time slots, we present delay optimal resource allocation algorithms in the heavy traffic regime. We study delay performance of our algorithms through simulations

Cost-Aware Resource Management for Decentralized Internet Services

Decentralized network services, such as naming systems, content distribution networks, and publish-subscribe systems, play an increasingly critical role and are required to provide high performance, low latency service, achieve high availability in the presence of network and node failures, and handle a large volume of users. Judicious utilization of expensive system resources, such as memory space, network bandwidth, and number of machines, is fundamental to achieving the above properties. Yet, current network services typically rely on less-informed, heuristic-based techniques to manage scarce resources, and often fall short of expectations. This thesis presents a principled approach for building high performance, robust, and scalable network services. The key contribution of this thesis is to show that resolving the fundamental cost-benefit tradeoff between resource consumption and performance through mathematical optimization is practical in large-scale distributed systems, and enables decentralized network services to meet efficiently system-wide performance goals. This thesis presents a practical approach for resource management in three stages: analytically model the cost-benefit tradeoff as a constrained optimization problem, determine a near-optimal resource allocation strategy on the fly, and enforce the derived strategy through light-weight, decentralized mechanisms. It builds on self-organizing structured overlays, which provide failure resilience and scalability, and complements them with stronger performance guarantees and robustness under sudden changes in workload. This work enables applications to meet system-wide performance targets, such as low average response times, high cache hit rates, and small update dissemination times with low resource consumption. Alternatively, applications can make the maximum use of available resources, such as storage and bandwidth, and derive large gains in performance. I have implemented an extensible framework called Honeycomb to perform cost-aware resource management on structured overlays based on the above approach and built three critical network services using it. These services consist of a new name system for the Internet called CoDoNS that distributes data associated with domain names, an open-access content distribution network called CobWeb that caches web content for faster access by users, and an online information monitoring system called Corona that notifies users about changes to web pages. Simulations and performance measurements from a planetary-scale deployment show that these services provide unprecedented performance improvement over the current state of the art

Towards Real-time Wireless Sensor Networks

Wireless sensor networks are poised to change the way computer systems interact with the physical world. We plan on entrusting sensor systems to collect medical data from patients, monitor the safety of our infrastructure, and control manufacturing processes in our factories. To date, the focus of the sensor network community has been on developing best-effort services. This approach is insufficient for many applications since it does not enable developers to determine if a system\u27s requirements in terms of communication latency, bandwidth utilization, reliability, or energy consumption are met. The focus of this thesis is to develop real-time network support for such critical applications. The first part of the thesis focuses on developing a power management solution for the radio subsystem which addresses both the problem of idle-listening and power control. In contrast to traditional power management solutions which focus solely on reducing energy consumption, the distinguishing feature of our approach is that it achieves both energy efficiency and real-time communication. A solution to the idle-listening problem is proposed in Energy Efficient Sleep Scheduling based on Application Semantics: ESSAT). The novelty of ESSAT lies in that it takes advantage of the common features of data collection applications to determine when to turn on and off a node\u27s radio without affecting real-time performance. A solution to the power control problem is proposed in Real-time Power Aware-Routing: RPAR). RPAR tunes the transmission power for each packet based on its deadline such that energy is saved without missing packet deadlines. The main theoretical contribution of this thesis is the development of novel transmission scheduling techniques optimized for data collection applications. This work bridges the gap between wireless sensor networks and real-time scheduling theory, which have traditionally been applied to processor scheduling. The proposed approach has significant advantages over existing design methodologies:: 1) it provides predictable performance allowing for the performance of a system to be estimated upon its deployment,: 2) it is possible to detect and handle overload conditions through simple rate control mechanisms, and: 3) it easily accommodates workload changes. I developed this framework under a realistic interference model by coordinating the activities at the MAC, link, and routing layers. The last component of this thesis focuses on the development of a real-time patient monitoring system for general hospital units. The system is designed to facilitate the detection of clinical deterioration, which is a key factor in saving lives and reducing healthcare costs. Since patients in general hospital wards are often ambulatory, a key challenge is to achieve high reliability even in the presence of mobility. To support patient mobility, I developed the Dynamic Relay Association Protocol -- a simple and effective mechanism for dynamically discovering the right relays for forwarding patient data -- and a Radio Mapping Tool -- a practical tool for ensuring network coverage in 802.15.4 networks. We show that it is feasible to use low-power and low-cost wireless sensor networks for clinical monitoring through an in-depth clinical study. The study was performed in a step-down cardiac care unit at Barnes-Jewish Hospital. This is the first long-term study of such a patient monitoring system