The Internet of Things (IoT) shall be able to incorporate transparently and seamlessly a large number of different and heterogeneous end systems, while providing open access to selected subsets of data for the development of a plethora of digital services. Building a general architecture for the IoT is hence a very complex task, mainly because of the extremely large variety of devices, link layer technologies, and services that may be involved in such a system. In this paper, we focus specifically to an urban IoT system that, while still being quite a broad category, are characterized by their specific application domain. Urban IoTs, in fact, are designed to support the Smart City vision, which aims at exploiting the most advanced communication technologies to support added-value services for the administration of the city and for the citizens. This paper hence provides a comprehensive survey of the enabling technologies, protocols, and architecture for an urban IoT. Furthermore, the paper will present and discuss the technical solutions and best-practice guidelines adopted in the Padova Smart City project, a proof-of-concept deployment of an IoT island in the city of Padova, Italy, performed in collaboration with the city municipality.

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Internet of Things for Smart Cities

Efficient application scheduling is critical for achieving high performance in heterogeneous computing environments. The application scheduling problem has been shown to be NP-complete in general cases as well as in several restricted cases. Because of its key importance, this problem has been extensively studied and various algorithms have been proposed in the literature which are mainly for systems with homogeneous processors. Although there are a few algorithms in the literature for heterogeneous processors, they usually require significantly high scheduling costs and they may not deliver good quality schedules with lower costs. In this paper, we present two novel scheduling algorithms for a bounded number of heterogeneous processors with an objective to simultaneously meet high performance and fast scheduling time, which are called the Heterogeneous Earliest-Finish-Time (HEFT) algorithm and the Critical-Path-on-a-Processor (CPOP) algorithm. The HEFT algorithm selects the task with the highest upward rank value at each step and assigns the selected task to the processor, which minimizes its earliest finish time with an insertion-based approach. On the other hand, the CPOP algorithm uses the summation of upward and downward rank values for prioritizing tasks. Another difference is in the processor selection phase, which schedules the critical tasks onto the processor that minimizes the total execution time of the critical tasks. In order to provide a robust and unbiased comparison with the related work, a parametric graph generator was designed to generate weighted directed acyclic graphs with various characteristics. The comparison study, based on both randomly generated graphs and the graphs of some real applications, shows that our scheduling algorithms significantly surpass previous approaches in terms of both quality and cost of schedules, which are mainly presented with schedule length ratio, speedup, frequency of best results, and average scheduling time metrics.

/pdf/performance-effective-and-low-complexity-task-scheduling-for-51tejcgo0m.pdf

Performance-effective and low-complexity task scheduling for heterogeneous computing

In the Hamadryas baboon, males are substantially larger than females. A troop of baboons is subdivided into a number of ‘one-male groups’, consisting of one adult male and one or more females with their young. The male prevents any of ‘his’ females from moving too far from him. Kummer (1971) performed the following experiment. Two males, A and B, previously unknown to each other, were placed in a large enclosure. Male A was free to move about the enclosure, but male B was shut in a small cage, from which he could observe A but not interfere. A female, unknown to both males, was then placed in the enclosure. Within 20 minutes male A had persuaded the female to accept his ownership. Male B was then released into the open enclosure. Instead of challenging male A , B avoided any contact, accepting A’s ownership.

Evolution and the Theory of Games

https://www.engr.colostate.edu/~hj/journals/71.pdf

A Comparison of Eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems

Multiple applications request data from multiple storage units over a computer network. The data is divided into segments and each segment is distributed randomly on one of several storage units, independent of the storage units on which other segments of the media data are stored. At least one additional copy of each segment also is distributed randomly over the storage units, such that each segment is stored on at least two storage units. This random distribution of multiple copies of segments of data improves both scalability and reliability. When an application requests a selected segment of data, the request is processed by the storage unit with the shortest queue of requests. Random fluctuations in the load applied by multiple applications on multiple storage units are balanced nearly equally over all of the storage units. This combination of techniques results in a system which can transfer multiple, independent high-bandwidth streams of data in a scalable manner in both directions between multiple applications and multiple storage units.

Computer system and process for transferring multiple high bandwidth streams of data between multiple storage units and multiple applications in a scalable and reliable manner

In most delay tolerant network (DTN) applications, mobile nodes utilize WiFi radios to obtain local information and transmit data. One bottleneck on DTN delivery performance is the short communication range of the WiFi radio. Rather than designing efficient protocols on WiFi based DTN, we propose a novel dual-radio architecture by adding a long-range low-bitrate eagle eye (EE) radio on every node. This EE radio can “see” real-time movement information of nodes in a significantly large range, and so much early scheduling can be done with this radio when compared with WiFi which is still in charge of data transmissions. Benefiting from this cooperative dual radios architecture, we design distributed EE routing protocol for minimizing delivery delay in DTNs. Through our prototype implementation with 7 EE devices and simulations based on real trace data of 4000 taxis in Shanghai, we show that the proposed architecture is able to achieve as low as 40% of the average delay with traditional DTNs.

Eagle eye: A dual-radio architecture in delay tolerant networks

In surveillance related Wireless Sensor Networks (WSNs) applications, mobile targets can utilize intelligent motion planning in robotics to avoid detection, which could impose great threats on the sensor field. In this paper, we propose countermeasures against mobile target motion planning. The proposed solution enables the sensors to interfere the localization and map generation on mobile targets so as to expose them in the sensor field. We compare the behaviors of a mobile target in naive mode, smart mode with Simultaneous Location And Mapping (SLAM) and interfered mode where sensor nodes use different puzzle algorithms to disturb it. The simulation results show that the puzzle algorithms can interfere SLAM on mobile targets and enhance the target detection performance in a WSN. We also build an experimental testbed with Iris motes and a mobile robot to validate our solution.

Interfering Mobile Target Motion Planning in Wireless Sensor Networks

Most existing on-demand video services, such as VoD, batching and patching, are not scalable. Although the near VoD service is scalable, it can provide only dozens of videos. A scalable video delivery paradigm, named scheduled video delivery (SVD), is described. In the SVD paradigm, users submit requests with specification of start time. The SVD system combines requests to form multicasting groups and schedules these groups to meet the deadline. SVD is not only scaled to the number of users but also to the number of video objects. Furthermore, SVD can serve more clients with mirroring proxies.

A scalable on-demand video delivery paradigm

The increasing number of vehicles nowadays makes traffic congestion problems, inefficient traffic management cannot solve the jam at intersection. In this paper, we propose an intelligent traffic control scheme which uses the dynamic traffic information. An improved algorithm is given to choose phase matrices for short-term throughput maximization by allocate more durations of green-sign to those flows with higher passing rate. Meanwhile, a new fairness strategy is designed to avoid the starvation problem and unnecessary stopping of vehicles. The simulation results are compared with both dynamic traffic control algorithm and dashboard traffic light algorithm show that the proposed scheme efficiently increases the throughput while keeping a relatively low average waiting time for vehicles.

An intelligent traffic control scheme with throughputmaximization and fairness strategy

Scalability is a key issue of on-line video service. Different methods have been proposed for the closed-loop video service, such as batching and patching. However, scalability itself has not been formally defined and the condition for a scalable system is not well studied yet. This paper studies scalability and the condition for scalable systems. It is found that when the arrival rate is across the threshold /spl Theta/ the system becomes scalable. This threshold value depends only on the number of videos, video length, and request distribution. We present an analysis for batching and patching. Comparison of batching, patching, and a new method, scheduled video delivery (SVD), is presented in this paper.

Min-You Wu

Papers

Eagle eye: A dual-radio architecture in delay tolerant networks

Interfering Mobile Target Motion Planning in Wireless Sensor Networks

A scalable on-demand video delivery paradigm

An intelligent traffic control scheme with throughputmaximization and fairness strategy

Scalability of closed-loop video delivery service