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

One task-flow scheduler has been designed to optimally allocate resources for a task-flow based Aircraft Collaborative Design Application in Optical Grid. This scheduler and application has been deployed on an Optical Grid testbed. The application’s practical running demonstrates its feasibility.

Demonstration of a Task-flow based Aircraft Collaborative Design Application in Optical Grid

The granularity of scheduling video streams can be categorized as cycle-scheduling and slot-scheduling where a time cycle is further divided into time slots. To avoid resource conflict and thereby increase throughput of clustered video servers, slot-scheduling using conflict-free scheduling and especially cycle-scheduling using full-duplex scheduling and ordered scheduling are presented in the paper. Also, the analysis of the pros and cons of applying slot-scheduling and cycle-scheduling on clustered video servers are discussed.

Efficient Algorithms for Slot-Scheduling and Cycle-Scheduling of Video Streams on Clustered Video Servers

In recent years, GPGPUs have experienced tremendous growth as general-purpose and high-throughput computing devices. However, irregular applications cannot fully utilize the hardware resource because of their plenty of control-flow divergences, irregular memory accesses and load imbalances. The lack of in-depth characterization and quantifying the ways in which irregular applications differ from regular ones on GPGPUs has prevented users from effectively making use of the hardware resource. We examine a suite of representative irregular applications on a cycle-accurate GPU simulator. We characterize their performance aspects and analyze the bottlenecks. We also assess the impact of changes in cache, DRAM and interconnect and discuss the implications for GPU architecture design. This work is useful in understanding and optimizing irregular applications on GPUs.

Microarchitectural characterization of irregular applications on GPGPUs

In this paper, we address the following problem: given a set of wireless nodes on the plane, what is the number of channels needed to ensure a schedulable conflict-free communication? While the exact number of channels needed is very difficult to compute, we focus on an upper bound for this number, in terms of the node density D. In particular, we derive several upper bounds in terms of D based on different settings of network interference ratio r, and analyze the trend of the upper bound as r changes. We also examine the tightness of our upper bound, by studying some specific scenarios of transmission. Our result can be viewed as another theoretical investigation towards the relationship between the network performance and the number of available channels. In practical application, the result suggests an easy estimation on the number of channels needed in the configuration of a wireless network. On the other hand, when the number of channels in a wireless system is given, the result can be used to provide a suggestion on the node density in the node deployment.

Upper Bound of The Number of Channels for Conflict-Free Communication in Multi-Channel Wireless Networks

Initialization is an indispensable process for wireless sensor networks since newly deployed sensors lack a reliable infrastructure for communication. Many efforts have been made to address the problem on initialization. However, most of them fall into the category of energy efficiency. In missioncritical scenarios, it is vital to reduce the initialization time in order to gather information as early as possible. In this paper, we study a new problem of accelerating initialization. First, we provide a novel parallel initialization mechanism that selects cluster heads before deployment and organizes singlehop clusters simultaneously after random deployment. Then, we prior-estimate that the number of cluster head candidates from n sensors is Θ (log n). Finally, simulation results show that these cluster head candidates can achieve the parallel initialization bounded by 16 time slots even for a large n.

Min-You Wu

Papers

Demonstration of a Task-flow based Aircraft Collaborative Design Application in Optical Grid

Efficient Algorithms for Slot-Scheduling and Cycle-Scheduling of Video Streams on Clustered Video Servers

Microarchitectural characterization of irregular applications on GPGPUs

Upper Bound of The Number of Channels for Conflict-Free Communication in Multi-Channel Wireless Networks

Accelerating Initialization for Sensor Networks