Goodbye, ALOHA!

©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The vision of the Internet of Things (IoT) to interconnect and Internet-connect everyday people, objects, and machines poses new challenges in the design of wireless communication networks. The design of medium access control (MAC) protocols has been traditionally an intense area of research due to their high impact on the overall performance of wireless communications. The majority of research activities in this field deal with different variations of protocols somehow based on ALOHA, either with or without listen before talk, i.e., carrier sensing multiple access. These protocols operate well under low traffic loads and low number of simultaneous devices. However, they suffer from congestion as the traffic load and the number of devices increase. For this reason, unless revisited, the MAC layer can become a bottleneck for the success of the IoT. In this paper, we provide an overview of the existing MAC solutions for the IoT, describing current limitations and envisioned challenges for the near future. Motivated by those, we identify a family of simple algorithms based on distributed queueing (DQ), which can operate for an infinite number of devices generating any traffic load and pattern. A description of the DQ mechanism is provided and most relevant existing studies of DQ applied in different scenarios are described in this paper. In addition, we provide a novel performance evaluation of DQ when applied for the IoT. Finally, a description of the very first demo of DQ for its use in the IoT is also included in this paper.Peer ReviewedPostprint (author's final draft

BriskStream: Scaling Data Stream Processing on Shared-Memory Multicore Architectures

We introduce BriskStream, an in-memory data stream processing system (DSPSs) specifically designed for modern shared-memory multicore architectures. BriskStream's key contribution is an execution plan optimization paradigm, namely RLAS, which takes relative-location (i.e., NUMA distance) of each pair of producer-consumer operators into consideration. We propose a branch and bound based approach with three heuristics to resolve the resulting nontrivial optimization problem. The experimental evaluations demonstrate that BriskStream yields much higher throughput and better scalability than existing DSPSs on multi-core architectures when processing different types of workloads.Comment: To appear in SIGMOD'1

Growth of relational model: Interdependence and complementary to big data

A database management system is a constant application of science that provides a platform for the creation, movement, and use of voluminous data. The area has witnessed a series of developments and technological advancements from its conventional structured database to the recent buzzword, bigdata. This paper aims to provide a complete model of a relational database that is still being widely used because of its well known ACID properties namely, atomicity, consistency, integrity and durability. Specifically, the objective of this paper is to highlight the adoption of relational model approaches by bigdata techniques. Towards addressing the reason for this in corporation, this paper qualitatively studied the advancements done over a while on the relational data model. First, the variations in the data storage layout are illustrated based on the needs of the application. Second, quick data retrieval techniques like indexing, query processing and concurrency control methods are revealed. The paper provides vital insights to appraise the efficiency of the structured database in the unstructured environment, particularly when both consistency and scalability become an issue in the working of the hybrid transactional and analytical database management system

Effect of steel fibre volume fraction on thermal performance of lightweight foamed mortar (LFM) at ambient temperature

Lightweight foamed mortar (LFM) has grow into utmost commercial building material in the construction industry for non-structural and semi-structural applications owing to its reduced self-weight, flowability, stability and excellent thermal insulation properties. Hence, this study was conducted with the aims to develop an alternative for conventional concrete bricks and blocks for non-structural and semi-structural applications of masonry. Lightweight foamed mortar (LFM) is either a cement paste or mortar, relegated as lightweight concrete, in which suitable foaming agent entraps the air-voids in mortar. It therefore has a wide range of applications such as material for wall blocks or panels, floor & roof screeds, trench reinstatement, road foundations and voids filling. This research focuses on experimental investigation of thermal properties of LFM with inclusion of relatively low volume fraction (0.2% and 0.4%) of steel fibre at ambient temperature. There are three parameters will be scrutinized such as thermal conductivity, thermal diffusivity as well as the specific heat capacity. There are two densities of 600kg/m3 and 1200kg/m3 had been cast and tested. The mix design proportion of LFM used for cement, aggregate and water ratio was 1: 1.5:0.45. The experimental results had indicated that the thermal conductivity, thermal diffusivity and specific heat value slightly higher than control mix due to the addition of steel fibres. For instance, thermal conductivity, diffusivity and specific heat of 600 kg/m3 density control mix were 0.212W/mK, 0.477mm2/s and 545 J/kg◦C respectively. When 0.2% volume fraction of steel fiber was added in the mix of 600 kg/m3 density, the value of thermal conductivity, diffusivity and specific heat were increased to 0.235W/mK, 0.583mm2/s and 578 J/kg◦C correspondingly. This is due to the characteristic of the steel fibre application in which steel fibre is good as heat conductor and excellent in absorbing heat. Therefore there is a potential of utilizing steel fiber in cement based material like LFM for components that needs excellent heat absorption capacity

Delay Contributing Factors and Strategies Towards Its Minimization in IoT

Internet of Things (IoT) refers to various interconnected devices, typically supplied with limited computational and communication resources. Most of the devices are designed to operate with limited memory and processing capability, low bandwidth, short range and other characteristics of low cost hardware. The resulting networks are exposed to traffic loss and prone to other vulnerabilities. One of the major concerns is to ensure that the network communication among these deployed devices remains at required level of Quality of Service (QoS) of different IoT applications. The purpose of this paper is to highlight delay contributing factors in Low Power and Lossy Networks (LLNs) since providing low end-to-end delay is a crucial issue in IoT environment especially for mission critical applications. Various research efforts in relevance to this aspect are then presente

Design and implementation of application-specific medium access control protocol for scalable smart home embedded systems

Thesis (M.S.) University of Alaska Fairbanks, 2016By incorporating electrical devices, appliances and house features in a system that is controlled and monitored either remotely or on-site, smart home technologies have recently gained an increasing popularity. There are several smart home systems already available, ranging from simple on-site home monitoring to self-learning and Wi-Fi enabled systems. However, current systems do not fully make use of recent technological advancement and synergy among a variable number of sensors for improved data collection. For a synergistic system to be provident it needs to be modular and scalable to match exact user needs (type of applications and adequate number of sensors for each application). With an increased number of sensors intelligently placed to optimize the data collection, a wireless network is indispensable for a flexible and inexpensive installation. Such a network requires an efficient medium access control protocol to sustain a reliable system, provide flexibility in design and to achieve lower power consumption. This thesis brings to light practical ways to improve current smart home systems. As the main contribution of this work, we introduce a novel application-specific medium access control protocol able to support suggested improvements. In addition, a smart home prototype system is implemented to evaluate the protocol performance and prove concepts of recommended advances. This thesis covers the design of the proposed novel medium access protocol and the software/hardware implementation of the prototype system focusing on the monitoring and data analysis side, while providing inputs for the control side of the system. The smart home system prototype is Wi-Fi and Web connected, designed and implemented to emphasize system usability and energy efficiency

Accurate and Resource-Efficient Monitoring for Future Networks

Monitoring functionality is a key component of any network management system. It is essential for profiling network resource usage, detecting attacks, and capturing the performance of a multitude of services using the network. Traditional monitoring solutions operate on long timescales producing periodic reports, which are mostly used for manual and infrequent network management tasks. However, these practices have been recently questioned by the advent of Software Defined Networking (SDN). By empowering management applications with the right tools to perform automatic, frequent, and fine-grained network reconfigurations, SDN has made these applications more dependent than before on the accuracy and timeliness of monitoring reports. As a result, monitoring systems are required to collect considerable amounts of heterogeneous measurement data, process them in real-time, and expose the resulting knowledge in short timescales to network decision-making processes. Satisfying these requirements is extremely challenging given today’s larger network scales, massive and dynamic traffic volumes, and the stringent constraints on time availability and hardware resources. This PhD thesis tackles this important challenge by investigating how an accurate and resource-efficient monitoring function can be realised in the context of future, software-defined networks. Novel monitoring methodologies, designs, and frameworks are provided in this thesis, which scale with increasing network sizes and automatically adjust to changes in the operating conditions. These achieve the goal of efficient measurement collection and reporting, lightweight measurement- data processing, and timely monitoring knowledge delivery