IOTSim: A simulator for analysing IoT applications

A disruptive technology that is influencing not only computing paradigm but every other business is the rise of big data. Internet of Things (IoT) applications are considered to be a major source of big data. Such IoT applications are in general supported through clouds where data is stored and processed by big data processing systems. In order to improve the efficiency of cloud infrastructure so that they can efficiently support IoT big data applications, it is important to understand how these applications and the corresponding big data processing systems will perform in cloud computing environments. However, given the scalability and complex requirements of big data processing systems, an empirical evaluation on actual cloud infrastructure can hinder the development of timely and cost effective IoT solutions. Therefore, a simulator supporting IoT applications in cloud environment is highly demanded, but such work is still in its infancy. To fill this gap, we have designed and implemented IOTSim which supports and enables simulation of IoT big data processing using MapReduce model in cloud computing environment. A real case study validates the efficacy of the simulator.     

NBA: novel bio-inspired algorithm for energy optimization in WSN for IoT applications

The Journal of Supercomputing - Wireless sensor networks (WSN) are the integral part of Internet of Things (IoT) applications. They consist of many sensor nodes energized by batteries. These...     

SIMON: A distributed computer architecture for intelligent patient monitoring

Intelligent real-time patient monitoring encompasses data acquisition and reduction, sensor validation, diagnosis, therapy advice, and selective display of information. This paper describes the architecture and the functionality of a prototype intelligent patient monitoring system, named SIMON, designed to meet these requirements. In SIMON, the various aspects of a monitoring task are performed by three semi-independent modules running asynchronously: the feature extraction, the patient model, and the display modules. Central to SIMON is the notion of context sensitivity which permits (a) the adaptation of the monitoring strategy in response to changes either in the patient state or in the monitoring equipment and (b) the contextual interpretation of incoming data. SIMON is currently applied to the task of monitoring newborn infants with respiratory distress syndrome (RDS) and undergoing assisted ventilation.     

HSIR: hybrid architecture for sensor identification and registration for IoT applications

Internet of things is the backbone of the smart applications, which attracts many types of research on the state-of-the-art network applications. Enormous research on sensor networks left more devices that are sensible in the day-to-day life. Hence, implementing new sensor networks for smart applications is not necessary. Many researchers have accepted and utilized existing networks for their request. In this case, techniques for identifying and registering existing sensible things are on demand. This paper proposed a hybrid framework for sensor identification and registration (HSIR) for new IoT applications. This research proposing HSIR as a framework aimed for user-friendliness in the IoT as well as addressed toward the scalability requirement of IoT applications. This model uses content- and context-based multicast communication instead of broadcast to reduce energy and time consumption in sensor identification. HSIR also proposed a public key to register the new network for application requirements. The behaviour of the proposed model has been assayed in realistic with simulations and proved by comparing other models.

     

Catalog of invisibility correlations for UbiComp and IoT applications

Requirements Engineering - The advance of Ubiquitous Computing (UbiComp) and Internet of Things (IoT) brought a new set of Non-Functional Requirements (NFRs), especially related to Human-Computer...     

Causal effect analysis-based intrusion detection system for IoT applications

International Journal of Information Security - Intrusion detection systems (IDSs) are employed at various levels in the network to either detect or prevent an intrusion that could cause...     

One round cipher algorithm for multimedia IoT devices

Multimedia Tools and Applications - With the exponential growth in Internet-of-Things (IoT) devices, security and privacy issues have emerged as critical challenges that can potentially compromise...     

A high speed algorithm for circular object location

This paper analyses how the Hough transform approach to circular object location could be speeded up by at least an order of magnitude — e.g. for certain low-cost automated inspection applications. Image sampling is found to be required and an effective but simply implemented strategy is devised which achieves speedup factors of up to 25 with real images. The algorithm is highly robust against shape defects and partial occlusions, and in addition robustness is easily monitored in practical situations.     

Location-based IoT applications on campus: The IoTtalk approach

The National Chiao Tung University is deploying several location-based IoT applications on campus based on an IoT device management platform called IoTtalk. The applications include dog tracking, emergency buttons, and indoor/outdoor environment conditions monitoring (PM2.5, temperature, CO₂, and so on). Some of the IoT devices for these applications have simple hardware structures to save energy, and therefore are not equipped with the positioning sensors (e.g., GPS or iBeacon). To support mobility management for these simple IoT devices, we develop a location finding mechanism in IoTtalk. By introducing the locator device in IoTtalk, we can effectively support mobility management for simple IoT devices that does not have location positioning capability. We describe how to develop the device applications to accommodate the location update feature, and show how to configure the location finding mechanism through the IoTtalk GUI. Then we conduct analytic analysis and simulation to investigate the accuracy of location tracking and power consumption for the dog tracking application.     

CQARPL: Congestion and QoS-aware RPL for IoT applications under heavy traffic

The Journal of Supercomputing - The Internet of Things (IoT) provides a common platform to connect the heterogeneous devices over the internet. Hence, the number of devices connected via the...     

Secure authenticated key exchange for WSNs in IoT applications

The Journal of Supercomputing - Wireless sensor networks (WSNs) are the key technological building block of Internet of Things (IoT), by which remote users can access the real-time data from the...     

Graph-based technique for survivability assessment and optimization of IoT applications

International Journal on Software Tools for Technology Transfer - The Internet of Things (IoT) has evolved from theoretical research to market deployment. The IoT will enable a plethora of new...     

Processing capacity-based decision mechanism edge computing model for IoT applications

The handling of complex tasks in IoT applications becomes difficult due to the limited availability of resources in most IoT devices. There arises a need to offload the IoT tasks with huge processing and storage to resource enriched edge and cloud. In edge computing, factors such as arrival rate, nature and size of task, network conditions, platform differences and energy consumption of IoT end devices impacts in deciding an optimal offloading mechanism. A model is developed to make a dynamic decision for offloading of tasks to edge and cloud or local execution by computing the expected time, energy consumption and processing capacity. This dynamic decision is proposed as processing capacity-based decision mechanism (PCDM) which takes the offloading decisions on new tasks by scheduling all the available devices based on processing capacity. The target devices are then selected for task execution with respect to energy consumption, task size and network time. PCDM is developed in the EDGECloudSim simulator for four different applications from various categories such as time sensitiveness, smaller in size and less energy consumption. The PCDM offloading methodology is experimented through simulations to compare with multi-criteria decision support mechanism for IoT offloading (MEDICI). Strategies based on task weightage termed as PCDM-AI, PCDM-SI, PCDM-AN, and PCDM-SN are developed and compared against the five baseline existing strategies namely IoT-P, Edge-P, Cloud-P, Random-P, and Probabilistic-P. These nine strategies are again developed using MEDICI with the same parameters of PCDM. Finally, all the approaches using PCDM and MEDICI are compared against each other for four different applications. From the simulation results, it is inferred that every application has unique approach performing better in terms of response time, total task execution, energy consumption of device, and total energy consumption of applications.     

Semantic service provisioning for smart objects: Integrating IoT applications into the web

Internet of Things (IoT) applications residing on the Web are the next logical development of the recent effort from academia and industry to design and standardize new communication protocols for smart objects. This paper proposes the service provisioning architecture for smart objects with semantic annotation to enables the integration of IoT applications into the Web. We aim to bring smart object services to the Web and make them accessible by plenty of existing Web APIs in consideration of its constraints such as limited resources (ROM, RAM, and CPU), low-power microcontrollers, and low-bitrate communication links.     

LICRA: A replicated-data management algorithm for distributed synchronous groupware applications

Replicated data consistency is a key issue in the design of distributed real time groupware applications. In this paper, we propose a new protocol to cope with this problem. The proposed algorithm guarantees an optimal response time while ensuring data consistency at system quiescence. The originality of our proposition relies on the fact that neither locks nor clocks nor global information are required to establish data consistency. Instead, direct dependency relations between generated operations as well as operation transformation mechanism are used. The coupling of the above two mentioned mechanisms is shown to realize a good trade-off between the different requirements of groupware applications. Advantages of our approach are illustrated by comparing the algorithm to two well known optimistic concurrency control protocols for groupware applications: dOPT and ORESTE.     

物联网应用中访问控制智能合约的形式化验证

蓝牙、WiFi等网络技术的进步推动物联网(IoT)的发展,然而IoT在方便了人们生活的同时也存在严重的安全隐患.若无安全的访问控制,非法接入IoT的访问可能给用户带来各方面的损失.传统的访问控制方法需要一个可信任的中心节点,不适合节点分散的IoT环境.区块链及智能合约的出现为IoT应用的访问控制提供了更有效的解决方案,...     

Adversarial android malware detection for mobile multimedia applications in IoT environments

Multimedia Tools and Applications - In this paper, we propose two defense methods against adversarial attack to a malware detection system for mobile multimedia applications in IoT environments....     

一种高速收敛粒子群优化算法

针对粒子群优化算法早熟问题,提出一种克服早熟的高速收敛粒子群算法．该算法首先采用混沌序列初始化粒子位置,以增强搜索多样性;其次,在算法中嵌入有效判断早熟停滞的方法,一旦检索到早熟迹象,便随机地选择最优解任意一维的分量值,用一个随机值取代它,以扰乱粒子的当前搜索轨迹,使其跳出局部最优．大量仿真实验表明,大多数连续函数的寻优过程只需用几个粒子、迭代几十次便能完成,可实现全局寻优过程的高速收敛．