Current Issue : January - March Volume : 2020 Issue Number : 1 Articles : 5 Articles
Spectrum sensing (SS) exhibits its advantages in the era of Internet of Things (IoT) due to \nlimited spectrum resource and a lower utilization rate of authorized spectrum. In consequence, the \nperformance improvement of SS seems a matter of great significance for the development of \nwireless communication and IoT. Motivated by this, this paper is devoted to multi -slot based SS in \nspecialty and several important conclusions are drawn. Firstly, SS with one slot outperforms those \nwith multiple slots if decision fusion rule is considered for multi -slot based SS. Secondly, multi -slot \nbased SS is conducive to the performance improvement of SS when instantaneous strong noise \noccurs in the radio environment. Thirdly, for multi -slot based cooperative spectrum sensing (CSS), \nmajority voting rule among multiple nodes obtains the optimal sensing performance. Both \ntheoretical analysis and simulation experiment validate the conclusions drawn in this paper....
The aim of this paper is to present DCM+, a new congestion control protocol\nfor data networks. It stands for Dynamic Congestion control for Mobile networks.\nNew metrics have been newly invented and introduced like normalized\nadvancing index (NAI) and complete transmission time (CTT). The simulations\nare done for a simple single-hop-topology (sender-router-receiver ). The\noutcomes of this protocol are excellent and, in most cases, better than other\napproaches. The excellent properties of our proposed protocol were possible\nthrough tracking the available slow-start threshold. We achieved performance\nimprovement, minimized end-to-end delay and large reduction in transmission\ntime. DCM+ was able to combine many advantages at same time of the\nprotocols NewReno and Westwood+. The results show, that DCM+ is extremely\nadequate for different types of networks. Feedback as main principle\nof control theory was used to control the congestion in the network. The parameters\nRound-Trip-Time (RTT) and Retransmission Timeout (RTO) are\nused as feedback signals to adjust the next congestion window (cwnd)....
An FSS based circular polarizer for high-speed wireless communication at 75\nGHz is presented. It has been designed on a low loss substrate with\ncross-dipole elements. Both simulation and measured results showed more\nthan 98% circular polarization at 75 GHz. Moreover, 3 dB axial-ratio bandwidth\nof 6.8 GHz (Simulation) and 7.8 GHz (Measured) has been achieved.\nThe proposed design has many advantages over the recently published research\nsuch as simplicity, low-profile, percentage bandwidth, frequency of\noperation and relative insertion loss....
Mobile crowdsourcing takes advantage of mobile devices such as smart phones and tablets to process data for a lot of applications\n(e.g., geotagging for mobile touring guiding monitoring and spectrum sensing). In this paper, we propose a mobile crowdsourcing\nparadigm to make a task requester exploit encountered mobile workers for high-quality results. Since a task may be too complex for\na single worker, it is necessary for a task requester to divide a complex task into several parts so that a mobile worker can finish a part\nof the task easily. We describe the task crowdsourcing process and propose the worker arrival model and task model. Furthermore,\nthe probability that all parts of the complicated task are executed by mobile workers is introduced to evaluate the result of task\ncrowdsourcing. Based on these models, considering computing capacity and rewards for mobile workers, we formulate a task\npartition problem to maximize the introduced probability which is used to evaluate the result of task crowdsourcing. Then, using a\nMarkov chain, a task partition policy is designed for the task requester to realize high-quality mobile crowdsourcing. With this task\npartition policy, the task requester is able to divide the complicated task into precise number of parts based on mobile workersâ??\narrival, and the probability that the total parts are executed by mobile workers is maximized. Also, the invalid number of task\nassignment attempts is analyzed accurately, which is helpful to evaluate the resource consumption of requesters due to probing\npotential workers. Simulations show that our task partition policy improves the results of task crowdsourcing....
We study how the graph structure of the Internet at the Autonomous Systems\n(AS) level evolved during a decade. For each year of the period 2008-2017 we\nconsider a snapshot of the AS graph and examine how many features related\nto structure, connectivity and centrality changed over time. The analysis of\nthese metrics provides topological and data traffic information and allows to\nclarify some assumptions about the models concerning the evolution of the\nInternet graph structure. We find that the size of the Internet roughly\ndoubled. The overall trend of the average connectivity is an increase over\ntime, while that of the shortest path length is a decrease over time. The internal\ncore of the Internet is composed of a small fraction of big AS and is more\nstable and connected the external cores. A hierarchical organization emerges\nwhere a small fraction of big hubs are connected to many regions with high\ninternal cohesiveness, poorly connected among them and containing AS with\nlow and medium numbers of links. Centrality measurements indicate that the\naverage number of shortest paths crossing an AS or containing a link between\ntwo of them decreased over time....
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