Overlay networks monitoring

The phenomenal growth of the Internet and its entry into many aspects of daily life has led to a great dependency on its services. Multimedia and content distribution applications (e.g., video streaming, online gaming, VoIP) require Quality of Service (QoS) guarantees in terms of bandwidth, delay, loss, and jitter to maintain a certain level of performance. Moreover, E-commerce applications and retail websites are faced with increasing demand for better throughput and response time performance. The most practical way to realize such applications is through the use of overlay networks, which are logical networks that implement service and resource management functionalities at the application layer. Overlays offer better deployability, scalability, security, and resiliency properties than network layer based implementation of services. Network monitoring and routing are among the most important issues in the design and operation of overlay networks. Accurate monitoring of QoS parameters is a challenging problem due to: (i) unbounded link stress in the underlying IP network, and (ii) the conflict in measurements caused by spatial and temporal overlap among measurement tasks. In this context, the focus of this dissertation is on the design and evaluation of efficient QoS monitoring and fault location algorithms using overlay networks. First, the issue of monitoring accuracy provided by multiple concurrent active measurements is studied on a large-scale overlay test-bed (PlanetLab), the factors affecting the accuracy are identified, and the measurement conflict problem is introduced. Then, the problem of conducting conflict-free measurements is formulated as a scheduling problem of real-time tasks, its complexity is proven to be NP-hard, and efficient heuristic algorithms for the problem are proposed. Second, an algorithm for minimizing monitoring overhead while controlling the IP link stress is proposed. Finally, the use of overlay monitoring to locate IP links\u27 faults is investigated. Specifically, the problem of designing an overlay network for verifying the location of IP links\u27 faults, under cost and link stress constraints, is formulated as an integer generalized flow problem, and its complexity is proven to be NP-hard. An optimal polynomial time algorithm for the relaxed problem (relaxed link stress constraints) is proposed. A combination of simulation and experimental studies using real-life measurement tools and Internet topologies of major ISP networks is conducted to evaluate the proposed algorithms. The studies show that the proposed algorithms significantly improve the accuracy and link stress of overlay monitoring, while incurring low overheads. The evaluation of fault location algorithms show that fast and highly accurate verification of faults can be achieved using overlay monitoring. In conclusion, the holistic view taken and the solutions developed for network monitoring provide a comprehensive framework for the design, operation, and evolution of overlay networks

Optimization Algorithms for Information Retrieval and Transmission in Distributed Ad Hoc Networks

An ad hoc network is formed by a group of self-configuring nodes, typically deployed in two or three dimensional spaces, and communicating with each other through wireless or some other media. The distinct characteristics of ad hoc networks include the lack of pre-designed infrastructure, the natural correlation between the network topology and geometry, and limited communication and computation resources. These characteristics introduce new challenges and opportunities for de- signing ad hoc network applications. This dissertation studies various optimization problems in ad hoc network information retrieval and transmission. Information stored in ad hoc networks is naturally associated with its location. To effectively retrieve such information, we study two fundamental problems, range search and object locating, from a distance sensitive point of view, where the retrieval cost depends on the distance between the user and the target information. We develop a general framework that is applicable to both problems for optimizing the storage overhead while maintaining the distance sensitive retrieval requirement. In addition, we derive a lowerbound result for the object locating problem which shows that logarithmic storage overhead is asymptotically optimal to achieve linear retrieval cost for growth bounded networks. Bandwidth is a scarce resource for wireless ad hoc networks, and its proper utilization is crucial to effective information transmission. To avoid conflict of wireless transmissions, links need to be carefully scheduled to satisfy various constraints. In this part of the study, we first consider an optimization problem of end-to-end on- demand bandwidth allocation with the single transceiver constraint. We study its complexity and present a 2-approximation algorithm. We then discuss how to estimate the end-to-end throughput under a widely adopted model for radio signal interference. A method based on identifying certain clique patterns is proposed and shown to have good practical performance

Real-Time Sensor Networks and Systems for the Industrial IoT

The Industrial Internet of Things (Industrial IoT—IIoT) has emerged as the core construct behind the various cyber-physical systems constituting a principal dimension of the fourth Industrial Revolution. While initially born as the concept behind specific industrial applications of generic IoT technologies, for the optimization of operational efficiency in automation and control, it quickly enabled the achievement of the total convergence of Operational (OT) and Information Technologies (IT). The IIoT has now surpassed the traditional borders of automation and control functions in the process and manufacturing industry, shifting towards a wider domain of functions and industries, embraced under the dominant global initiatives and architectural frameworks of Industry 4.0 (or Industrie 4.0) in Germany, Industrial Internet in the US, Society 5.0 in Japan, and Made-in-China 2025 in China. As real-time embedded systems are quickly achieving ubiquity in everyday life and in industrial environments, and many processes already depend on real-time cyber-physical systems and embedded sensors, the integration of IoT with cognitive computing and real-time data exchange is essential for real-time analytics and realization of digital twins in smart environments and services under the various frameworks’ provisions. In this context, real-time sensor networks and systems for the Industrial IoT encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges. The ten articles in this Special Issue describe advances in real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. In the relevant landscape, the domain of wireless networking technologies is centrally positioned, as expected

Real-time communication platfrom for wireless cyber-physical applications

A Cyber-Physical System (CPS) is a physical system whose operations are monitored, coordinated, and controlled by computation and communication processes. Applying wireless technologies to cyber-physical systems can significantly enhance the system mobility and reduce the deployment and maintenance cost. Existing wireless technologies, however either cannot provide real-time or probabilistic guarantee on packet delivery or are not fast enough to support desired application requirements. Nondeterministic packet transmission and insufficiently high sampling rate will severely hurt application performance. To address this problem, we propose a real-time wireless communication platform called RT-WiFi. In this dissertation, we present our design and implementation of the data link layer and network management framework of RT-WiFi platform that provides predictable packet delivery and high sampling rate. The RT-WiFi communication platform is designed to support configurable components for adjusting design trade-offs including sampling rate, latency variance, reliability and thus can serve as a suitable communication platform for supporting a wide range of wireless CPS applications. Based on the RT-WiFi management platform, we further propose advanced network management techniques to provide jitter-free scheduling algorithm for improving system performance and to support reliable data transmission in noisy environments. To evaluate the effectiveness of our proposed algorithms and to verify the efficiency of our network management platform, we conduct a series of experiments and a case study that integrate the RT-WiFi communication platform with a health care CPS application to investigate the application performance in the real world.Computer Science

Scratchpad Memory Management For Multicore Real-Time Embedded Systems

Multicore systems will continue to spread in the domain of real-time embedded systems due to the increasing need for high-performance applications. This research discusses some of the challenges associated with employing multicore systems for safety-critical real-time applications. Mainly, this work is concerned with providing: 1) efficient inter-core timing isolation for independent tasks, and 2) predictable task communication for communicating tasks. Principally, we introduce a new task execution model, based on the 3-phase execution model, that exploits the Direct Memory Access (DMA) controllers available in modern embedded platforms along with ScratchPad Memories (SPMs) to enforce strong timing isolation between tasks. The DMA and the SPMs are explicitly managed to pre-load tasks from main memory into the local (private) scratchpad memories. Tasks are then executed from the local SPMs without accessing main memory. This model allows CPU execution to be overlapped with DMA loading/unloading operations from and to main memory. We show that by co-scheduling task execution on CPUs and using DMA to access memory and I/O, we can efficiently hide access latency to physical resources. In turn, this leads to significant improvements in system schedulability, compared to both the case of unregulated contention for access to physical resources and to previous cache and SPM management techniques for real-time systems. The presented SPM-centric scheduling algorithms and analyses cover single-core, partitioned, and global real-time systems. The proposed scheme is also extended to support large tasks that do not fit entirely into the local SPM. Moreover, the schedulability analysis considers the case of recovering from transient soft errors (bit flips caused by a single event upset) in several levels of memories, that cannot be automatically corrected in hardware by the ECC unit. The proposed SPM-centric scheduling is integrated at the OS level; thus it is transparent to applications. The proposed scheme is implemented and evaluated on an FPGA platform and a Commercial-Off-The-Shelf (COTS) platform. In regards to real-time task communication, two types of communication are considered. 1) Asynchronous inter-task communication, between either sequential tasks (single-threaded) or parallel tasks (multi-threaded). 2) Intra-task communication, where parallel threads of the same application exchange data. A new task scheduling model for parallel tasks (Bundled Scheduling) is proposed to facilitate intra-task communication and reduce synchronization overheads. We show that the proposed bundled scheduling model can be applied to several parallel programming models, such as fork-join and DAG-based applications, leading to improved system schedulability. Finally, intra-task communication is governed by a predictable inter-core communication platform. Specifically, we propose HopliteRT, a lean and predictable Network-on-Chip that connects the private SPMs