Abstract-Fog computing preserves benefits of cloud computing and is strategically positioned to address effectively many local and performance issues because its resources and specific services are virtualized and located at the edge of the customer premises. Resource management is a critical issue affecting system performance significantly. Due to the complex distribution and high mobility of fog devices, computation resources still experience high latencies in fog's large coverage area. This paper considers a Fog-based Region and Cloud (FBRC) in which requests are locally handled not just by a region but multiple regions when additional resources are needed. An efficient task scheduling mechanism is thus essential to minimize the completion time of tasks and improve user experiences. To this end, two issues are investigated in the paper: 1) designing a fog-based region architecture to provide nearby computing resources; 2) investigating efficient scheduling algorithms to distribute tasks among regions and remote clouds. To deal with the complexity of scheduling tasks, a heuristic-based algorithm is proposed based on our formulation and validated by extensive simulations.
Abstract-In the age of Internet of Things (IoT), sensors form a foundational component of IoT services, yet they are rigid with little capability for programmable configuration or reusability as they are application-specific, manufacturer-specific. Emerging IoT applications often deploy a vast number of sensors which may serve multiple applications. Programmability is thus essential but not found in legacy or current generation sensors. It is challenging to effectively utilize heterogeneity of resources to handle a large number of application demands. Software defined networking and network functions virtualization have proved effective paradigms for provisioning services on-demand and managing network functions and their life cycles. This paper proposes a software defined IoT architecture that captures the spirit of SDN and NFV where a software-defined Internet of Things (SD-IoT) controller can provide services as requested by an application and also manage heterogeneous physical sensors through their virtual representation called software-defined virtual sensor (SD-VSensor) autonomously. In particular, the paper presents the design of a streamline SD-IoT controller, a lightweight and reconfigurable SD-VSensor, and the communication protocol (S-MANAGE) between them. The proposed architecture enables heterogeneous applicationspecific WSN systems to be recognized and effectively utilized by diverse IoT applications under the orchestration of the SD-IoT controller. Moreover, heterogeneity of sensor nodes or IoT devices can be programmed to achieve sensor services on demand. The preliminary implementation results demonstrate the feasibility and efficiency of the proposed architecture.
Cloud computing and cloud services provide an alternative IT infrastructure and service models for users. The users use cloud to store their data, delegate the management of the data, and deploy their services cost-effectively. This usage model, however, raised a number of concerns relating to data control, data protection and data mobility: 1) users may lose control of their resource; 2) data protection schemes are not adequate when data is moved to a new cloud; 3) tracking and tracing changes of data location as well as accountability of data operations are not well supported. To address these issues, this paper proposes a novel cloud service for data mobility from two aspects: data mobility and data protection. A data mobility service is designed and implemented to manage data mobility and data traceability. A Location Register Database (LRD) is also developed to support the service. Furthermore, data is protected by a data security service CPRBAC (Cloud-based Privacy-aware Role Based Access Control) and an Auditing service that are capable of verifying data operations and triggering alarms on data violations in the Cloud environment.
We propose, implement, and evaluate a pervasive sensing system that is capable of collecting data from sensors that may surround a user in a given setting. Such systems will enable creation of new types of applications that span across devices, users, and domains based on spatial, temporal, and social aggregations of sensor data. Key innovation in our work is a sensing fabric that collects data from a variety of sensors and leverages platform-integrated sensors, which are built into hosting devices, such as laptops and tablets. These sensors can significantly improve sensing in enterprise settings and they are comparatively inexpensive to manufacture, deploy, and maintain. Our system embodies three key architectural principles: (1) support for a variety of sensor types including platform-integrated sensors for pervasive sensing, (2) use of Internet protocols for sensor connectivity, web technologies and programming model for application development, and (3) use a hybrid sensor database design with a document-oriented component to improve flexibility and performance. We evaluate our implementation in real-world pilots for several months and 73 users. Our results demonstrate that platform-integrated sensors can provide accurate sensing data, have negligible impact on operations of a hosting platform, and that our architecture can provide sensing services across users and devices over a sustained period of time.
Cloud computing dramatically reduces the expense and complexity of managing IT systems. Business customers do not need to invest in their own costly IT infrastructure, but can delegate and deploy their services effectively to cloud vendors and service providers. A number of security and protection mechanisms have been proposed to prevent the disclosure of sensitive information or tempering with the data by employing various policy, encryption, and monitoring approaches. However, few efforts have been focused on data mobility issues in terms of protection of data when it is moved within a cloud or to and from a new cloud environment. To allay users' concern of data control, data ownership, security and privacy, we propose a novel data mobility management model which ensures continuity protecting data at new cloud hosts at new data locations. The model provides a mobility service to handle data moving operation that relies on a new location database service. The new model allows the establishment of a proxy supervisor in the new environment and the ability of the active data to record its own location. The experimental outcomes demonstrate the feasibility, proactivity, and efficiency by the full mobility management model.
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