Joint energy and throughput optimization for MEC-enabled multi-UAV IoRT networks

In this paper, we study an Unmanned Aerial Vehicle (UAV) enabled Mobile Edge Computing (MEC) service provisioning to the Internet of Remote Things (IoRT) devices spread randomly on the ground in a remote area. The data generated by the IoRT devices is collected by the UAVs, which immediately relay the data collected to an MEC device installed on the ground at a nearby location. The MEC device receives the data from the UAVs, and sends the results back to the UAVs, which in turn relay them to IoRT devices. We aim to minimize the energy consumption by the IoRT devices and the UAVs, while maximizing the system throughput subject to bandwidth, power, information-causality, and UAVs’ trajectory constraints. We formulate the problem as a Mixed Integer Non Linear Programming problem, which is a complex and non-convex optimization problem. To make the problem tractable, we use variable relaxation. We further develop an iterative algorithm based on Block Coordinate Descent method, to jointly optimize the connection scheduling, power control, bit transmission scheduling, bandwidth allocation, and trajectories of the UAVs. Numerical results demonstrate the convergence of the algorithm and superiority of the proposed model with respect to conventional methods. Our proposed system model of placing MEC at ground shows 9% improvement in energy consumption when compared to carrying out computations at MEC carried by UAV and a 99% improvement when compared to placing MEC at the satellite. The proposed system model shows a 0.2% lower system throughput on average, compared to placing MEC at UAV, which is tolerable considering gains in terms of energy consumption

Improving DTN Routing Performance Using Many-to-Many Communication: A Performance Modeling Study

Abstract-Delay-Tolerant Networks (DTNs) have emerged as an exciting research area with a number of useful applications. Most of these applications would benefit greatly by a reduction in the message delivery delay experienced in the network. The delay performance of DTNs is adversely affected by contention, especially severe in the presence of higher traffic rates and node densities. Many-to-Many (M2M) communication can handle this contention much better than traditional oneto-one communication employing CSMA. In this paper, for the first time, we analytically model the expected delivery delay of a DTN employing epidemic routing and M2M communication. The accuracy of our model is demonstrated by matching the analytical results against those from simulations. We also show using simulations that M2M communication significantly improves the delay performance (with respect to one-to-one CSMA) for highcontention scenarios. We believe our work will enable the effective application of M2M communication to reduce delivery delays in DTNs

Improving Capacity and Energy Efficiency of Femtocell Based Cellular Network Through Cell Biasing

Abstract-Future of cellular networks lies in heterogeneity. Heterogeneous cellular networks are characterized by overlay of low power nodes such as microcells, picocells, and femtocells along with traditional macrocell base stations. These nodes help operators to improve system capacity in cost effective manner while making the environment greener by reducing the carbon footprint. Research has shown that femtocells can be an effective solution to handle the increasing demands for indoor mobile traffic. However, low utilization of femtocell resources limits the gain obtained from their large scale deployment. Also, random placement of femtocells accumulate additional interference to macrocell users. In this paper, we introduce the concept of cell biasing for femtocells to improve user association and resource utilization. Our work analyses the effects of cell biasing on femtocell based cellular network and provides improvement in capacity and energy efficiency of the network through frequency reuse and subchannel power control. The obtained analytical results are verified through simulation

Demand based State Aware Channel Reconfiguration Algorithm for Multi-Channel Multi-Radio Wireless Mesh Networks

Efficient utilization of Multi Channel - Multi Radio (MC-MR) Wireless Mesh Networks (WMNs) can be achieved only by intelligent Channel Assignment (CA) and Link Scheduling (LS). Due to the dynamic nature of traffic demand in WMNs, the CA has to be reconfigured whenever traffic demand changes, in order to achieve maximum throughput in the network. The reconfiguration of CA requires channel switching which leads to disruption of ongoing traffic in the network. The existing CA algorithms for MC-MR WMNs in the literature do not consider the channel reconfiguration overhead that occurs due to this channel switching. In this paper, we propose a novel reconfiguration framework that considers both network throughput and reconfiguration overhead to quantitatively evaluate a reconfiguration algorithm. Based on the reconfiguration framework, we propose an online heuristic algorithm for CA called Demand based State Aware channel Reconfiguration Algorithm (DeSARA) that finds the CA for the current traffic demand by considering the existing CA of the network to minimize the reconfiguration overhead. We show through simulations that DeSARA outperforms both static CA and fully dynamic CA in terms of total achieved throughput

Alcohol use and burden for 195 countries and territories, 1990-2016 : a systematic analysis for the Global Burden of Disease Study 2016

Background Alcohol use is a leading risk factor for death and disability, but its overall association with health remains complex given the possible protective effects of moderate alcohol consumption on some conditions. With our comprehensive approach to health accounting within the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we generated improved estimates of alcohol use and alcohol-attributable deaths and disability-adjusted life-years (DALYs) for 195 locations from 1990 to 2016, for both sexes and for 5-year age groups between the ages of 15 years and 95 years and older. Methods Using 694 data sources of individual and population-level alcohol consumption, along with 592 prospective and retrospective studies on the risk of alcohol use, we produced estimates of the prevalence of current drinking, abstention, the distribution of alcohol consumption among current drinkers in standard drinks daily (defined as 10 g of pure ethyl alcohol), and alcohol-attributable deaths and DALYs. We made several methodological improvements compared with previous estimates: first, we adjusted alcohol sales estimates to take into account tourist and unrecorded consumption; second, we did a new meta-analysis of relative risks for 23 health outcomes associated with alcohol use; and third, we developed a new method to quantify the level of alcohol consumption that minimises the overall risk to individual health. Findings Globally, alcohol use was the seventh leading risk factor for both deaths and DALYs in 2016, accounting for 2.2% (95% uncertainty interval [UI] 1.5-3.0) of age-standardised female deaths and 6.8% (5.8-8.0) of age-standardised male deaths. Among the population aged 15-49 years, alcohol use was the leading risk factor globally in 2016, with 3.8% (95% UI 3.2-4-3) of female deaths and 12.2% (10.8-13-6) of male deaths attributable to alcohol use. For the population aged 15-49 years, female attributable DALYs were 2.3% (95% UI 2.0-2.6) and male attributable DALYs were 8.9% (7.8-9.9). The three leading causes of attributable deaths in this age group were tuberculosis (1.4% [95% UI 1. 0-1. 7] of total deaths), road injuries (1.2% [0.7-1.9]), and self-harm (1.1% [0.6-1.5]). For populations aged 50 years and older, cancers accounted for a large proportion of total alcohol-attributable deaths in 2016, constituting 27.1% (95% UI 21.2-33.3) of total alcohol-attributable female deaths and 18.9% (15.3-22.6) of male deaths. The level of alcohol consumption that minimised harm across health outcomes was zero (95% UI 0.0-0.8) standard drinks per week. Interpretation Alcohol use is a leading risk factor for global disease burden and causes substantial health loss. We found that the risk of all-cause mortality, and of cancers specifically, rises with increasing levels of consumption, and the level of consumption that minimises health loss is zero. These results suggest that alcohol control policies might need to be revised worldwide, refocusing on efforts to lower overall population-level consumption.Peer reviewe