Sharif Digital Repository

The basic idea of this paper is about sharing the extra space of the local storage with other devices in an IoT network, and on the other hand, using the corresponding space from devices that don’t utilize their storage enough.As a result, all IoT devices in the network can access a larger (and of course a bit slower) unified storage and each device can consume nearly as much space as needed, regardless of its limited local storage.This paper demonstrates a design to achieve such a shared storage in local IoT network. Furthurmore, a minimal (yet complete) system is implemented in the form of an SDK as a proof of concept.As an example for the effect of the current design on an IoT network, in... 

Collaborative edge computing (CEC) is a recently popular paradigm enabling sharing of computation resources among different edge devices. In CEC, multiple stakeholders (mobile users, mobile edge computing servers, cloud servers,...) collaborate to provide new computation capacity in order to perform computation-intensive tasks efficiently in the edge. In the thesis, each task, the data that should be computed in the cloud or edge, was modeled as a graph of dependent sub-tasks. Resource allocation for task offloading is an important problem to address in CEC as we need to decide when and where each subtask is executed. In this work, we mathematically formulate the problem of resource... 

With the explosion of mobile smart devices, many computation intensive applications have emerged, such as interactive gaming and augmented reality. Mobile edge computing (EC) is put forward, as an extension of cloud computing, to meet the low-latency require- ments of the applications. In mobile edge computing systems, an edge node may have a high load when a large number of mobile devices offload their tasks to it. those offloaded tasks may experience large processing delay or even be dropped when their deadlines expire. Due to the uncertain load dynamics at the edge nodes, it is challenging for each device to determine its offloading decision (i.e., whether to offload or not, and which... 

Mobile edge computing (MEC) is a promising technology that aims to resolve cloud computing’s issues by deploying computation resources at the edge of mobile network and in the proximity of users. The advantages of MEC include reduced latency, energy consumption, and load on access and mobile core networks, to name but a few. Despite all the aforementioned advantages, the mobility of mobile network users causes the traditional MEC architecture to suffer from several issues, such as decreased efficiency and frequent service interruption. One of the methods to manage users’ mobility is virtual machine (VM) migration, where the VM containing the user’s task is migrated to somewhere closer to... 

In order to use the high performance capabilities of a computing system, first it is required to provide a proper modelling for the job and the system's environment. Second, it is required to design scheduling and offloading algorithms based on the job and the system modeling and third for evaluating the performance of these algorithms. It is needed to either simulate them or prove their approximation factors. This project aims to carry out these three parts for the Edge Computing environment. The laid out model of the system in this thesis consists of many devices that are distributed around the network, which they can execute tasks parallel to each other, and between each two devices there... 

Based on fog computing paradigm, new applications have become feasible through the use of hardware capabilities of smart phones. Many of these applications require a vast amount of computing and real-time execution should be guaranteed. Based on fog computing, in order to solve these problems in is necessary to offload heavy computing to servers with adequate hardware capabilities. On the other side, the offloading process causes time overhead and endangers the real-timeliness of the application. Also, because of the limited battery capacity of the handheld devices, energy consumption is very important and should be minimized.The usual proposed solution for this problem is to refactor the... 

Optimizing and reducing energy consumption will be a feature of smart cities in the future. In addition to the technical aspects of a technology, one of the most important obstacles to its lack of development is not considering economic factors. Investigating the economics and calculating the cost of using IoT systems in the energy sectors of a smart city is one of the most important issues. Using existing systems in buildings or adding limited and inexpensive hardware to make a building smart can make smartening a cost-effective operation and more widespread. In this research, a proposed architecture based on edge processing is described. In addition to receiving and displaying camera... 

With the growing trend of IoT, especially in critical areas like health system and city management, and the expectations of even higher growth with the advent of 5G networks, the security and preserving of users' privacy in IoT has gained significant importance. Anomaly detection is one of the approaches to monitor IoT devices which enables the identification of anomalous behaviors. This anomalous behavior could indicate malware infection, physical malfunctions, or tampering.Deep learning has been a common approach for anomaly detection for the past few years. The solutions are mostly suggested in a special purpose manner and because they are based on a particular deep learning model, they... 

The main idea of the upcoming research is to provide a way of benefiting from processing at the edge and processing in the fog for the open source platform openremote; In such a way that the central core of the platform can offload its processing tasks to the edge of the network. With this work, a large amount of the processes that used to be done by the core will be offloaded from the core. On the other hand, by applying processes at the edge of the network, it becomes possible to eliminate a large amount of overhead caused by raw data transmission, and as a result, the productivity of the network increases. In the current research, in addition to designing a model to add the mentioned... 

IoT-based systems use cloud computing servers that are generally far away from them to perform tasks. Whenever there is a computational task that requires heavy and complex processing, the problem of offloading decision is to identify the best computing server to perform the processing related to this task. Numerous dynamic factors affect the solution to this problem.Optimization in energy consumption of the device that has generated a task alongside reducing its calculation delay can be applied in solving the offloading problem. The optimization problem that is formed to minimize the energy consumption in the offloading decision is an integer programming problem that is generally difficult... 

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... 

Routing requests to cloud service providers has been increasingly used to provide powerful computations for users. In order to reduce the long delays of cloud computations, mobile edge computing architecture has been proposed, where computing nodes are placed in the vicinity of the network edge. Data-driven applications such as IoT, remote virtual reality, and self-driving cars require not only computational resources but also memory resources in edge service providers. Since service providers in mobile edge computing architecture have much more limited resources compared to cloud space, in this research, we propose a solution to maximize the profit of service providers while providing... 

With the increasing number of elderly people as a proportion of the total population in the world and the aging of the world's population, the need for medical care has increased. On the one hand, most of the elderly population have chronic diseases such as diabetes, hypertension, etc., which do not require hospitalization in healthcare centers, but they need to monitor their health status. Given the progress of technology, the measurement of vital body signals has been made possible with non-invasive methods. In this thesis, an attempt has been made to provide a wearable and portable solution for the measurement, monitoring, and collection of vital signals based on the Internet of Things... 

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... 

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... 

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... 

The emerging applications of machine learning algorithms on mobile devices motivate us to offload the computation tasks of training a model or deploying a trained one to the cloud or at the edge of the network. One of the major challenges in this setup is to guarantee the privacy of the client data. Various methods have been proposed to protect privacy in the literature. Those include (i) adding noise to the client data, which reduces the accuracy of the result, (ii) using secure multiparty computation (MPC), which requires significant communication among the computing nodes or with the client, (iii) relying on homomorphic encryption (HE) methods, which significantly increases computation... 

Cloud computing has a significant role in expanding applications of the Internet of Things (IoT). Currently, applications such as virtual reality and augmented reality require low latency, which is not achievable using traditional cloud computing in some scenarios. Edge computing is a new approach in IoT, which solves some of the limitations of the cloud computing by extending and developing its operations. Reducing response time and network traffic are some of the most important achievements of edge computing. Despite of its numerous advantages over cloud computing, edge computing faces serious challenges such as virtualization, implementation infrastructure, resource allocation and task... 

Mobile edge computing (MEC) is envisioned to address the computation demands of Internet of Things (IoT) devices. However, it is crucial for the MEC to operate in coordination with the cloud tier to achieve a highly scalable IoT system. In addition, IoT devices require regular maintenance to either recharge or replace their batteries which may not always be feasible. Wireless energy transfer (WET) can provide IoT devices a stable source of energy. Nonetheless, proper scheduling of energy harvesting and efficient allocation of computing resources are the key for sustainable operation of these devices. In this thesis, we introduce a three-tier wireless powered mobile edge computing (WPMEC)...