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

The capacity of wireless ad hoc networks is mainly restricted by the number of concurrent transmissions. Recent studies found that multi-packet reception (MPR) can increase the number of concurrent transmissions and improve network capacity. This paper studies the capacity of 2-D wireless networks wherein each node can decode at most k simultaneous transmissions within its receiving range. We call such networks k-MPR wireless networks. For comparison, we call traditional networks 1-MPR wireless networks. Suppose that the number of nodes in a wireless network is n and each node can transmit at W bits/sec. For arbitrary k-MPR wireless networks, we show that when k = O(n), the capacity gain over 1-MPR networks is Theta(radickappa). When k = Omega(n), the capacity is Theta(W n) bit-meters/sec and the network is scalable. For random k-MPR wireless networks, we show that when k = O(radic(log n)), the capacity upper bound and lower bound match and the capacity gain over 1-MPR networks is Theta(kappa). When k = Omega(radic(log n)), even the lower bound has a capacity gain of Theta(radic(log n)) over 1-MPR networks. From these results, we conclude that the main constraints for k-MPR wireless networks to utilize MPR ability are the limited number of transmitters and the limited number of flows served by each node.

/pdf/on-the-capacity-of-k-mpr-wireless-networks-2uxw5cvby1.pdf

On the capacity of κ-MPR wireless networks

This paper introduces WiBEST, Wireless Body and Environmental Sensor Tracking platform, for personal indoor positioning. WiBEST is built with portable on-body sensor nodes and assisted sensor nodes deployed in the targeted indoor area. It takes a hybrid approach with pedestrian dead reckoning and radio-based localization and explore the their cooperative efforts. Real-time inertial measurements are combined with RSSI-based information, and then processed with an Extended Kalman Filter to be weighted in the location estimation according to their reliability. WiBEST also incorporates with an adaptive Step Length Algorithm to reduce the deviation of the measurements.The experimentation results show that WiBEST can improve the accuracy of the positioning by 66.3% compared to pure inertial solution. With the popularity of wearable devices with inertial sensors and wireless communication chips, we believe that this approach is very promising for personal indoor positioning services.

WiBEST: A hybrid personal indoor positioning system

Applying directional antennas in wireless ad hoc networks offers numerous benefits, such as extended communication range, increased spatial reuse, improved capacity and suppressed interference. However, directional antennas can cause new location-dependent carrier sensing problems, such as new hidden terminal and deafness problems, which can cause severe penalties to the performance. Recently, a few schemes have been proposed to tackle these problems. However, these methods can provide limited solutions on the hidden terminal and deafness problems. We propose a new MAC protocol, termed the busy-tone based directional medium access control (BT-DMAC) protocol. When the transmission is in progress, the sender and the receiver will turn on their omnidirectional busy tones to protect the transmission. By combining with directional network allocation vector (DNAV), the scheme almost mitigates the hidden and the deafness problems completely. The mechanism increases the probability of successful data transmission and consequently improves the network throughput. This paper describes the BT- DMAC scheme and analyzes its performance. The simulation results also demonstrate the effectiveness of the protocol.

A Busy-Tone Based MAC Scheme for Wireless Ad Hoc Networks Using Directional Antennas

In wireless sensor networks (WSNs), since many basic scientific works heavily rely on the complete sensory data, data recovery is an indispensable operation against the data loss. Several works have studied the missing value problem. However, existing solutions cannot achieve satisfactory accuracy due to special loss patterns and high loss rates in WSNs. In this work, we propose a multiple attributes-based recovery algorithm which can provide high accuracy. Firstly, based on two real datasets, the Intel Indoor project and the GreenOrbs project, we reveal that such correlations are strong, e.g., the change of temperature and light illumination usually has strong correlation. Secondly, motivated by this observation, we develop a Multi-Attribute-assistant Compressive-Sensing-based (MACS) algorithm to optimize the recovery accuracy. Finally, real trace-driven simulation is performed. The results show that MACS outperforms the existing solutions. Typically, MACS can recover all data with less than 5% error when the loss rate is less than 60%. Even when losing 85% data, all missing data can be estimated by MACS with less than 10% error.

Min-You Wu

Papers

On the capacity of κ-MPR wireless networks

WiBEST: A hybrid personal indoor positioning system

A Busy-Tone Based MAC Scheme for Wireless Ad Hoc Networks Using Directional Antennas

Multiple attributes-based data recovery in wireless sensor networks

A new paradigm for urban surveillance with vehicular sensor networks