Sharif Digital Repository

Nowadays, one of the challenges in the field of bioinformatics is the excess processed data volume such that this data volume resulted from a complete genome sequence of a species can be up to hundreds gigabytes. Every time that we talk about increasing data volume, data storage, transforming, and the process will become of interest. Moreover, considering the presence of portable sequencer devices in the market and the limitations of process outside of the lab environments, this problem becomes of more critical importance. Fortunately, due to the nature of the genome data and their redundancy, specific algorithms to compress them have been introduced to the market. In this thesis, we chose... 

Recently, portable genome sequencing devices have been introduced to the market, which have also made it possible to provide these services in remote locations or outside the laboratory. The amount of raw data from the readings of a sequencer for the entire genome of a human or plant can be in the hundreds of gigabytes, making it difficult and expensive to maintain and transfer to the center for such sequencing. Fortunately, these readings have a lot of redundancy, and many new algorithms have been proposed to compress them based on the intrinsic properties of this data. Sequencing devices were mainly used in the laboratory environment, which naturally had virtually unlimited access to urban... 

Automatic Speech Recognition (ASR) systems are a significant part of Personal Assistants in mobile phones. But because of the time-dependent nature of ASR systems, they are computation and memory-intensive tasks. On the other hand, mobile devices utilize a Low-Power design to extend battery life and improve user experience, making them incompatible with heavy-loaded tasks such as ASR systems. For instance, if we run an inference with a 60 seconds audio file on a well-known open-sourced Speech Recognition System named DeepSpeech, it will only take 49 seconds for a desktop PC to generate the results. Still, a mobile phone with ARM64 architecture with the same input file will take 92 seconds to... 

Google Inc. states that, 400 million Android-powered devices have been activated and used by people until 2012. This rapid growth of Android operating system in mobile phones and other electronic devices makes it very important to improve the efficiency of this Operating System. Dalvik is the underlying virtual machine (VM) in Android that executes Android-based applications, and hence, its performance directly affects Android-powered devices. De-virtualization is a technique to improve performance of VMs. In this method, VM’s instructions (bytecode) are natively and directly executed by hardware. In addition, de-virtualization technique eliminates the software interpretation/translation... 

The applications that consist ofprecedence-constrained parallel taskshave used in business activities and scientific projects and the energy consumption of these application has become a major concern in datacenters. At the software level, energy-aware task scheduling algorithmsare an effective technique for energy reduction and optimizing performance in data centers. The related works in this areahave traditionally ignore the utilization value of physical machines (PMs) and while the main reason of the energy inefficiency in datacenters is low average utilization of the PMs.In this paper, we propose a new energy-aware scheduling (EASy) algorithm forprecedence-constrained parallel taskswith... 

Rapid growth and proliferation of cloud computing services around the world has increased the necessity and significance of improving the energy efficiency of could implementations. Virtual machines (VM) comprise the backend of most, if not all, cloud computing services. Several VMs are often consolidated on a physical machine to better utilize its resources. We take into account the network structure of the data center hosting the physical machines when consolidating the VMs so that fewer racks and routers are employed, without compromising the service-level agreements, so that unused routing and cooling equipment can be turned off to reduce energy consumption. Our experimental results,... 

In recent years, the demands come to data centers have increased significantly, so huge amount of energy consumption, cost of this usage and environmental effects of data centers have become serious issues. Accordingly using solar energy to provide some portion of a data center’s energy usage can reduce environmental effects efficiently. Also smarter use of this energy could decrease overall cost of energy in data center. The demands that come to a data center are categorized to critical and non-critical workloads. Running of Non-critical workload (batch job) can be moved to another time according to its deadline. This work suggests a solution that schedules batch jobs considering solar... 

Ever-increasing development and growth of information volume is an unprecedented phenomenon. Analyzing and saving such enormous volume of information calls for innovative ideas capable of processing and managing this information. One of the successful projects in this regard done by Apache is known as Hadoop.Hadoop is a popular open-source implementationof MapReduce processing schemefor analysis of large datasets. The heart of Hadoop is MapReduce that is a parallel programming model for data processing on clusters. To handle storage resources across the cluster, Hadoop employs a distributeduser-level filesystem. The Hadoop Distributed File System (HDFS) is written in Java and is designed for... 

Forecasts predict that the volume of digital data will increase by 300 times in 2020 compared with 2005. This significant growth further emphasizes the importance of Big Data as well as Big Data Processing. MapReduce and its open source implementation Hadoop are prevailing frameworks for implementing Big Data Analytics and applications. Because of inherently huge amount of data and computational requirements of Big Data applications, acquisition of large amount of computational resources is necessary. However, managing in-house clusters to respond the computational requirements is costly such that small- and middle-sized companies either cannot afford it, or find cloud-based solutions... 

Virtualization has provided good and efficient use of resources in today datacenters. In this environment, modules of multi-tier applications can run on several Virtual Machines (VMs). VMs that are dedicated to a module often need to transfer data among themselves, and also to the VMs in other modules, and hence, the overall application runtime may be increased if the communicating VMs are put on far physical machines; consequently, servers must be up for a longer time and will consume more energy. Consolidating several VMs on a single Physical Machine (PM) effectively reduces the total computing power consumption, but we show that it is also important to consider the above inter-VM... 

In the past few years, data centers energy consumption and their maintenance costs have become an important issue in technology world. Server consolidation using virtualization and VM live migration allows cloud data centers to improve resource utilization and hence energy efficiency. In order to save energy, consolidation techniques try to turn off the idle servers, while because of workload fluctuations, these offline servers should be turned on to support the increased resource demands. These repeated on-off cycles could affect the hardware reliability and wear-and-tear of servers and increase the maintenance and replacement costs. On the other hand, over-aggressive strategies would... 

With the proliferation of data centers, their ever-growing energy consumption has gained lots of attention from both academy and industry . Two primary parts that use majority of energy in data centers are IT equipment and cooling system or Computing Room Air Conditioning (CRAC) unit. Energy consumption of cooling system strongly relies on thermal performance of data center. Therefore, applying thermal management techniques for decreasing energy consumption of CRAC is a common practice. Moreover, the energy consumption of IT equipment affects the energy consumption of CRAC directly. Demand for more computing resources in data centers and their physical limits has, motivated the use of FPGAs ... 

MapReduce and its open source implementation, Hadoop, are the prevailing platforms for big data processing. MapReduce is a simple programming model for performing large computational problems in large-scale distributed systems. This model consists of two major phases: Map and Reduce. Between these two main phases, partitioner part is embedded which distributes produced keys by Map tasks among Reduce tasks When the amount of keys and their associated values, which are called intermediate data, is huge, this part has significant impact on execution time of Reduce tasks, and consequently, completion time of jobs. In this paper, we present a network and resource aware key partitioner to decrease... 

With the emergence of the 5th generation cellular networks, response time is becoming increasingly more important. One of the solutions to satisfy this requirement is using mobile edge computing. MEC is bringing the cloud computing features to the edge of the network and reduces services response time by reducing the user distance to her services. But for this solution to be effective, we need to migrate user services based on their movements. The main problem in migrating services is predicting user route and do the migration based on these predictions. We must do this procedure in a way that minimizes the service outage. In this research, we predict the user route with the historical... 

Today, the significant growth of virtual and computer communications is clear to everyone. Naturally, the inputs and outputs of all these communications is Data. Creating and using data is considered to be so important that new sciences such as data science have been developed to analyze this phenomenon. As we know the main source of all data that we can deal with throughout the day are Data centers and Data warehouses. A data center is where many servers are in operation and never shut down during the day and night. Consequently, there are several concerns due to rapid growth of data centers all over the world. The main concern is the amount of energy consumption that causes damage to the... 

In the near future, we will see a new generation of cellular networks called 5G. Due to the growing number of users and applications, cloud computing does not provide users needs. Edge servers can be used at radio base stations for this purpose. Edge server is a limited processing unit that allows users to perform their processing operations as close as possible. Therefore, the distance between the user and the service will be reduced and as a result the response time is greatly decreased.Cloud-based services are supported by specific software that are deployed in a virtual machine. The number of virtual machines of different applications is fewer than the number of edge servers in the... 

With the emergence of 5G networks, response time is becoming increasingly more important. 5G networks facilitate usage of Mobile Edge Computing. MEC provides computing capabilities at the edges of cellular networks. Since the computational capability in mobile devices is limited, running high performance applications using external resources is a way to overcome this limitation. Workload offloading in MEC is an approach that provides additional computation capability for users to meet the desired response time. In this study, we presented a Mixed Integer Non-Linear Programing model for offloading different workloads on a heterogeneous set of MEC servers to minimize the SLA violations. We... 

Regular monitoring of health factors such as blood pressure and glucose is essential to manage human health. In many such software applications, the patients have to manually enter the value sensed by medical devices such as glucometers into the app. According to medical specialists, this procedure has several drawbacks: (1) Entering values by patients, several times in a day is bothersome, and makes users leave the app, (2) due to the direct intervention of the patient in the procedure, it is error-prone, and besides, (3) users tend to enter unrealistic values. With edge computing, cloud infrastructures, and mobile phones which are ubiquitous and can capture images, it is now possible to... 

Refractory metals (W,Re,Ta,Mo,Nb) and their alloys can exhibit exceptional properties at elevated temperatures. However, refectory metals tend to be relatively heavy and, in some cases, can be relatively difficult to form in complex shapes at low cost. Light composites of refractory metals with high-melting ceramics, which can be fabricated into dense, near net shapes at low temperatures, would be particularly attractive for advanced aerospace applications. In this project, WC powders have been pressed and shaped to cylindrical preforms. Secondly, these performs have been sintered slightly(presintered) into porous, rigid ones with about 50% open porosity. Finally, in order to reach dense... 

Advances in semiconductor manufacturing technologies have enabled us to build billions of transistors on a single die. However, the increasing amount of process variation in nanometer technologies has made it inevitable to move toward statistical analysis methods, instead of deterministic worst-case-based techniques, at all design levels. In this project, we studied the problem of variation-aware task scheduling for MPSoCs. To this end, we first proposed a variability analysis framework to analyze the effect of process variation on the main parameters of MPSoCs. Then, to solve the MPSoC task scheduling problem, we proposed two metaheuristic variation-aware task scheduling method based on...