Backlog-based random access in wireless networks : fluid limits and delay issues

We explore the spatio-temporal congestion dynamics of wireless networks with backlog-based random-access mechanisms. While relatively simple and inherently distributed in nature, suitably designed backlog-based access schemes provide the striking capability to match the optimal throughput performance of centralized scheduling algorithms in a wide range of scenarios. In the present paper, we show that the specific activity functions for which maximum stability has been established, may however yield excessive queue lengths and delays. The results reveal that more aggressive/persistent access schemes can improve the delay performance, while retaining the maximum stability guarantees in a rich set of scenarios. In order to gain qualitative insights and examine stability properties we will investigate fluid limits where the system dynamics are scaled in space and time. As it turns out, several distinct types of fluid limits can arise, exhibiting various degrees of randomness, depending on the structure of the network, in conjunction with the form of the activity functions. We further demonstrate that, counter to intuition, additional interference may improve the delay performance in certain cases. Simulation experiments are conducted to illustrate and validate the analytical findings

Backlog-based random access in wireless networks : fluid limits and delay issues

We explore the spatio-temporal congestion dynamics of wireless networks with backlog-based random-access mechanisms. While relatively simple and inherently distributed in nature, suitably designed backlog-based access schemes provide the striking capability to match the optimal throughput performance of centralized scheduling algorithms in a wide range of scenarios. In the present paper, we show that the specific activity functions for which maximum stability has been established, may however yield excessive queue lengths and delays. The results reveal that more aggressive/persistent access schemes can improve the delay performance, while retaining the maximum stability guarantees in a rich set of scenarios. In order to gain qualitative insights and examine stability properties we will investigate fluid limits where the system dynamics are scaled in space and time. As it turns out, several distinct types of fluid limits can arise, exhibiting various degrees of randomness, depending on the structure of the network, in conjunction with the form of the activity functions. We further demonstrate that, counter to intuition, additional interference may improve the delay performance in certain cases. Simulation experiments are conducted to illustrate and validate the analytical findings

Performance Comparison of Contention- and Schedule-based MAC Protocols in Urban Parking Sensor Networks

Network traffic model is a critical problem for urban applications, mainly because of its diversity and node density. As wireless sensor network is highly concerned with the development of smart cities, careful consideration to traffic model helps choose appropriate protocols and adapt network parameters to reach best performances on energy-latency tradeoffs. In this paper, we compare the performance of two off-the-shelf medium access control protocols on two different kinds of traffic models, and then evaluate their application-end information delay and energy consumption while varying traffic parameters and network density. From the simulation results, we highlight some limits induced by network density and occurrence frequency of event-driven applications. When it comes to realtime urban services, a protocol selection shall be taken into account - even dynamically - with a special attention to energy-delay tradeoff. To this end, we provide several insights on parking sensor networks.Comment: ACM International Workshop on Wireless and Mobile Technologies for Smart Cities (WiMobCity) (2014

An adaptive scaling mechanism for managing performance variations in network functions virtualization: A case study in an NFV-based EPC

The scaling is a fundamental task that allows addressing performance variations in Network Functions Virtualization (NFV). In the literature, several approaches propose scaling mechanisms that differ in the utilized technique (e.g., reactive, predictive and machine learning-based). The scaling in NFV must be accurate both at the time and the number of instances to be scaled, aiming at avoiding unnecessary procedures of provisioning and releasing of resources; however, achieving a high accuracy is a non-trivial task. In this paper, we propose for NFV an adaptive scaling mechanism based on Q-Learning and Gaussian Processes that are utilized by an agent to carry out an improvement strategy of a scaling policy, and therefore, to make better decisions for managing performance variations. We evaluate our mechanism by simulations, in a case study in a virtualized Evolved Packet Core, corroborating that it is more accurate than approaches based on static threshold rules and Q-Learning without a policy improvement strategy

تحسين التخزين المؤقت في شبكات المعلومات المركزية (خوارزمية احتمالية محسنة)

ICN (Information Central Networks) is an appropriate alternative to the current Internet, focusing on distributing and retrieving content rather than transferring data between devices over the network. ICN networks follow a specific approach in which caches are used instead of transferring information across network paths from source to consumers. The main objective of the article is to implement a probability storage algorithm that takes into account two criteria (content popularity - distance ratio between nodes and source) to achieve the following objectives: 1. Increase  the speed of storage. 2. Reduce the cache replacement rate responsible for serving users. 3. Reduced delivery times. In this article we present a preliminary comparison by simulators to create the proposed probability caching algorithm and demonstrate the gains made by this algorithm. تشكل شبكات المعلومات المركزية ICN (Information Central Networks) بديل مناسب لشبكة الانترنت الحالية حيث تركز على توزيع واستعادة المحتوى بدلاً من نقل البيانات بين الأجهزة عبر الشبكة. تتبع شبكات ال ICN نهج معين تستخدم من خلاله الذواكر المخبئية (Cache) بدلاً من نقل المعلومات عبر المسارات الشبكية من المصدر الى المستخدمين. الهدف الرئيسي من البحث هو تطبيق خوارزمية تخزين احتمالية تأخذ بعين الاعتبار معيارين اثنين (شعبية المحتوى – نسبة المسافة بين العقد والمصدر) لتحقيق الاهداف التالية: 1-                زيادة سرعة التخزين المؤقت. 2-                تخفيض معدل استبدال ال Cache المسؤولة عن تخديم المستخدمين. 3-                تخفيض عدد مرات تسليم المحتوى. نقدم في هذه البحث مقارنة أولية من خلال المحاكات لعمل خوارزمية التخزين المؤقت الاحتمالية المقترحة وإظهار الفوائد التي تقدمها هذه الخوارزمية

Structuring Time through Participation in Micro-task Crowdsourcing: A Time Allocation Perspective

Small payments in micro-task crowdsourcing markets appear unreasonable compared with remunerations for regular work in the workplace, yet hundreds of thousands of micro-tasks are completed each day, and frequently by highly educated individuals. To explain this perplexing anomaly, we investigate individuals’ continuous participation in micro-task crowdsourcing from a time allocation perspective. Drawing upon the theory of the allocation of time, relative advantage over alternative activities and reservation wage of micro-task crowdsourcing affect intent to continue and expected wage respectively, which in turn have effects on intent to increase participation level. Based on previous research on time structure, we propose time structure as another indicator of continuous participation in micro-task crowdsourcing. More importantly, the negative moderating effect of time is conjectured as a salient driver of continuous participation in micro-task crowdsourcing. IT-enabled time structuring thus helps individuals fill dead time with micro-tasking online in spite of low payments