No Arabic abstract
In this paper, we argue that existing concepts for the design and implementation of network stacks for constrained devices do not comply with the requirements of current and upcoming Internet of Things (IoT) use cases. The IoT requires not only a lightweight but also a modular network stack, based on standards. We discuss functional and non-functional requirements for the software architecture of the network stack on constrained IoT devices. Then, revisiting concepts from the early Internet as well as current implementations, we propose a future-proof alternative to existing IoT network stack architectures, and provide an initial evaluation of this proposal based on its implementation running on top of state-of-the-art IoT operating system and hardware.
Recently, Internet service providers (ISPs) have gained increased flexibility in how they configure their in-ground optical fiber into an IP network. This greater control has been made possible by (i) the maturation of software defined networking (SDN), and (ii) improvements in optical switching technology. Whereas traditionally, at network design time, each IP link was assigned a fixed optical path and bandwidth, modern colorless and directionless Reconfigurable Optical Add/Drop Multiplexers (CD ROADMs) allow a remote SDN controller to remap the IP topology to the optical underlay on the fly. Consequently, ISPs face new opportunities and challenges in the design and operation of their backbone networks. Specifically, ISPs must determine how best to design their networks to take advantage of the new capabilities; they need an automated way to generate the least expensive network design that still delivers all offered traffic, even in the presence of equipment failures. This problem is difficult because of the physical constraints governing the placement of optical regenerators, a piece of optical equipment necessary for maintaining an optical signal over long stretches of fiber. As a solution, we present an integer linear program (ILP) which (1) solves the equipment-placement network design problem; (2) determines the optimal mapping of IP links to the optical infrastructure for any given failure scenario; and (3) determines how best to route the offered traffic over the IP topology. To scale to larger networks, we also describe an efficient heuristic that finds nearly optimal network designs in a fraction of the time. Further, in our experiments our ILP offers cost savings of up to 29% compared to traditional network design techniques.
Based on software-defined principles, we propose a holistic architecture for Cyberphysical Systems (CPS) and Internet of Things (IoT) applications, and highlight the merits pertaining to scalability, flexibility, robustness, interoperability, and cyber security. Our design especially capitalizes on the computational units possessed by smart agents, which may be utilized for decentralized control and in-network data processing. We characterize the data flow, communication flow, and control flow that assimilate a set of components such as sensors, actuators, controllers, and coordinators in a systemic programmable fashion. We specifically aim for distributed and decentralized decision-making by spreading the control over several hierarchical layers. In addition, we propose a middleware layer to encapsulate units and services for time-critical operations in highly dynamic environments. We further enlist a multitude of vulnerabilities to cyberattacks, and integrate software-defined solutions for enabling resilience, detection, and recovery. In this purview, several controllers cooperate to identify and respond to security threats and abnormal situations in a self-adjusting manner. Last, we illustrate numerical simulations in support of the virtues of a software-defined design for CPS and IoT.
The rapid deployment of Internet of Things (IoT) applications leads to massive data that need to be processed. These IoT applications have specific communication requirements on latency and bandwidth, and present new features on their generated data such as time-dependency. Therefore, it is desirable to reshape the current IoT architectures by exploring their inherent nature of communication and computing to support smart IoT data process and analysis. We introduce in this paper features of IoT data, trends of IoT network architectures, some problems in IoT data analysis, and their solutions. Specifically, we view that software-defined edge computing is a promising architecture to support the unique needs of IoT data analysis. We further present an experiment on data anomaly detection in this architecture, and the comparison between two architectures for ECG diagnosis. Results show that our method is effective and feasible.
The evolution of software defined networking (SDN) has played a significant role in the development of next-generation networks (NGN). SDN as a programmable network having service provisioning on the fly has induced a keen interest both in academic world and industry. In this article, a comprehensive survey is presented on SDN advancement over conventional network. The paper covers historical evolution in relation to SDN, functional architecture of the SDN and its related technologies, and OpenFlow standards/protocols, including the basic concept of interfacing of OpenFlow with network elements (NEs) such as optical switches. In addition a selective architecture survey has been conducted. Our proposed architecture on software defined heterogeneous network, points towards new technology enabling the opening of new vistas in the domain of network technology, which will facilitate in handling of huge internet traffic and helps infrastructure and service providers to customize their resources dynamically. Besides, current research projects and various activities as being carried out to standardize SDN as NGN by different standard development organizations (SODs) have been duly elaborated to judge how this technology moves towards standardization.
As network size continues to grow exponentially, there has been a proportionate increase in the number of nodes in the corresponding network. With the advent of Internet of things (IOT), it is assumed that many more devices will be connected to the existing network infrastructure. As a result, monitoring is expected to get more complex for administrators as networks tend to become more heterogeneous. Moreover, the addressing for IOTs would be more complex given the scale at which devices will be added to the network and hence monitoring is bound to become an uphill task due to management of larger range of addresses. This paper will throw light on what kind of monitoring mechanisms can be deployed in internet of things (IOTs) and their overall effectiveness.