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.

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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

Hypertool: A Programming Aid for Multicomputers.

Multi-Packet Reception (MPR) enables simultaneous receptions from different transmitters to a single receiver, which has been demonstrated to bring capacity improvement in wireless network. However, MPR does not improve the transmission capability of intermediate relay nodes in a multi-hop routing and thus these nodes may become the bottlenecks for increasing throughput despite of great reception capability. We investigate the scheduling for multi-hop routing with MPR to improve the network throughput under multiple data flows. We formulate the optimization problem under K-MPR model and analyze the performance upper bound with ideal scheduling. We propose a distributed scheduling scheme based on a k-Connected k-Dominating Set backbone to eliminate bottleneck effects on intermediate relay nodes as to enhance the network throughput. We show the effectiveness of our scheme by comparing its performance with the upper bound and node-disjoint routing.

Enhancing Throughput in Wireless Multi-Hop Network with Multiple Packet Reception

In this paper, we propose a FPGA-based parallel algorithm to compute the transitive closure of the relation matrix on a fixed-size PE array. Experimental results showed that speedup increases with the problem size. The speedup against a single PE is between 11.3 and 195.9. Compared to a general CPU solution, this algorithm achieves acceleration rate of 3.7 and 376 under the worst and best situations, respectively.

FPGA based parallel transitive closure algorithm

In this paper, we present a multi-objective Integer Linear Program (ILP) for the joint throughput optimization and traffic engineering problem in Wavelength-Division Multiplexing (WDM) networks. The proposed model simultaneously maximizes the aggregated throughput, minimizes the resource consumption, and achieves load balancing by minimizing the maximum link utilization (MLU). Even though the ILP is NP-hard, we demonstrate its application in a 14-node network. In addition to the ILP, we propose a heuristic algorithm which can be implemented in a distributed manner. The proposed algorithm addresses the multi-objective problem as an e-constraint problem, upper bounding the per-route resource consumption and maximizing the throughput by routing through multiple widest paths. Performance studies show that, by considering the multiple objectives simultaneously, the solutions of the ILP are better than those obtained by optimizing a single objective only. At the same time, the throughput of the heuristic is close to optimal, and load balancing is achieved. Furthermore, its resource consumption is nearly the same as the one obtained by the shortest path algorithm, which is optimal when only resource consumption is considered.

A multi-objective approach for throughput optimization and traffic engineering in WDM networks

In wireless sensor networks, the nodes near the sink suffer from heavy traffic load. The recent progresses in physical layer make multi-packet reception (MPR) feasible, which may alleviate the suffering nodes. In this paper, we utilize MPR to improve the throughput of wireless sensor networks while maintain the fairness requirement for each sensor. Firstly, we formulate an optimization problem for wireless sensor networks using MPR. The result of the optimization is an upper bound for the network throughput. Secondly, we give a feasible heuristic scheme. In the performance evaluation, we analyse the throughput gap between the upper bound and the performance of the heuristic scheme. We also study the performance of the heuristic scheme by adjusting several network parameters and the results show that MPR brings notable throughput gain in wireless sensor networks and give some network design implications.

Min-You Wu

Papers

Hypertool: A Programming Aid for Multicomputers.

Enhancing Throughput in Wireless Multi-Hop Network with Multiple Packet Reception

FPGA based parallel transitive closure algorithm

A multi-objective approach for throughput optimization and traffic engineering in WDM networks

On the Throughput of Wireless Sensor Networks Using Multi-Packet Reception