Sum Of Energy Consumption Research Articles

A novel energy-aware utility maximization for efficient device-to-device communication in LTE-WiFi networks under mixed traffic scenarios

To meet the ever increasing data traffic demand from Device-to-Device (D2D) users, more mobile broadband bandwidth will be needed. Given the large amount of spectrum available in the unlicensed band, it is now being considered by the cellular operators as a complementary tool to augment their service offering. However, due to the uncontrollable interference from collocated WiFi networks, the available bandwidth for the D2D users cannot be guaranteed. In this paper, we introduce an approach for resource allocation to D2D users by aggregating spectrum resources from both licensed and unlicensed bands. An optimization framework that maximizes the utility functions of all the D2D pairs while minimizing the overall energy consumption when transmitting on licensed and unlicensed bands is proposed. Since the aforementioned spectrum and power allocation problem is NP-hard in nature, we therefore, propose a two-step framework for resource allocation to D2D pairs. In the first step, an efficient resource (LTE Resource Blocks (RBs) and unlicensed subchannels) assignment scheme is obtained by formulating a convex optimization problem, which maximizes the aggregate utility of D2D pairs while maintaining fixed transmission power on all the RBs/unlicensed subchannels. In the next step, a non-linear programming problem that maximizes the aggregate utility over sum energy consumption is formulated based on the spectrum resource allocation results obtained from the previous step. The optimization problem determines the transmission power on all the allocated RBs/subchannels by using primal-dual decomposition theory and the gradient update method. As a result of this, we observe that a user and the resource preferences can be considered while performing resource allocation. We further observe that in a network comprising of two category of users (viz., one who have subscribed to real time Quality of Service (QoS) services and second who have subscribed to Best Effort (BE) services), the proposed resource allocation scheme gives priority to QoS services when allocating resources. Extensive simulations and comparison with various benchmark schemes show that aggregating both licensed and unlicensed resources indeed improves the utility of the D2D pairs.

Energy-Efficient Resource Allocation for Secure NOMA-Enabled Mobile Edge Computing Networks

Mobile edge computing (MEC) has been envisaged as a promising technique in the next-generation wireless networks. In order to improve the security of computation tasks offloading and enhance user connectivity, physical layer security and non-orthogonal multiple access (NOMA) are studied in MEC-aware networks. The secrecy outage probability is adopted to measure the secrecy performance of computation offloading by considering a practically passive eavesdropping scenario. The weighted sum-energy consumption minimization problem is firstly investigated subject to the secrecy offloading rate constraints, the computation latency constraints and the secrecy outage probability constraints. The semi-closed form expression for the optimal solution is derived. We then investigate the secrecy outage probability minimization problem by taking the priority of two users into account, and characterize the optimal secrecy offloading rates and power allocations with closed-form expressions. Numerical results demonstrate that the performance of our proposed design are better than those of the alternative benchmark schemes.

UAV-Assisted Relaying and Edge Computing: Scheduling and Trajectory Optimization

In this paper, we study an unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) architecture, in which a UAV roaming around the area may serve as a computing server to help user equipment (UEs) compute their tasks or act as a relay for further offloading their computation tasks to the access point (AP). We aim to minimize the weighted sum energy consumption of the UAV and UEs subject to the task constraints, the information-causality constraints, the bandwidth allocation constraints and the UAV's trajectory constraints. The required optimization is nonconvex, and an alternating optimization algorithm is proposed to jointly optimize the computation resource scheduling, bandwidth allocation, and the UAV's trajectory in an iterative fashion. Numerical results demonstrate that significant performance gain is obtained over conventional methods. Also, the advantages of the proposed algorithm are more prominent when handling computation-intensive latency-critical tasks.

Optimal Task Offloading Scheduling for Energy Efficient D2D Cooperative Computing

This letter investigates energy-efficient computation offloading designs for device-to-device (D2D) cooperative computing between the two users, in which each user has time-varying computation task arrivals. In this setup, the two users can dynamically exchange the computation loads via D2D offloading for reducing the overall energy consumption. In particular, we minimize the weighted sum-energy consumption of both users over a finite time horizon, by jointly optimizing their local computing and task exchange (offloading) decisions over time, subject to the newly introduced task causality and completion constraints. By applying the convex optimization technique, we obtain the well-structured optimal solution to this problem. Numerical results show that by enabling bidirectional computation sharing between the users, the proposed D2D cooperative computing design significantly reduces the system energy consumption, as compared with other benchmark schemes.

Multi-Antenna NOMA for Computation Offloading in Multiuser Mobile Edge Computing Systems

This paper studies a multiuser mobile edge computing (MEC) system in which one base station (BS) serves multiple users with intensive computation tasks. We exploit the multi-antenna non-orthogonal multiple access (NOMA) technique for multiuser computation offloading, such that different users can simultaneously offload their computation tasks to the multi-antenna BS over the same time/frequency resources, and the BS can employ successive interference cancelation (SIC) to efficiently decode all users’ offloaded tasks for remote execution. In particular, we pursue energy-efficient MEC designs by considering two cases with partial and binary offloading, respectively. We aim to minimize the weighted sum-energy consumption at all users subject to their computation latency constraints, by jointly optimizing the communication and computation resource allocation as well as the BS’s decoding order for SIC. For the case with partial offloading, the weighted sum-energy minimization is a convex optimization problem, for which an efficient algorithm based on the Lagrange duality method is presented to obtain the globally optimal solution. For the case with binary offloading, the weighted sum-energy minimization corresponds to a mixed Boolean convex optimization problem that is generally more difficult to be solved. We first use the branch-and-bound (BnB) method to obtain the globally optimal solution and then develop two low-complexity algorithms based on the greedy method and the convex relaxation, respectively, to find suboptimal solutions with high quality in practice. Via numerical results, it is shown that the proposed NOMA-based computation offloading design significantly improves the energy efficiency of the multiuser MEC system as compared to other benchmark schemes. It is also shown that for the case with binary offloading, the proposed greedy method performs close to the optimal BnB-based solution, and the convex relaxation-based solution achieves a suboptimal performance but with lower implementation complexity.

Exploiting Physical-Layer Security for Multiuser Multicarrier Computation Offloading

This letter considers a mobile edge computing system with one access point (AP) serving multiple users over a multicarrier channel, in the presence of a malicious eavesdropper. In this system, each user can execute the respective computation tasks by partitioning them into two parts, which are computed locally and offloaded to AP, respectively. We exploit the physical-layer security to secure the multiuser computation offloading from being overheard by the eavesdropper. Under this setup, we minimize the weighted sum-energy consumption for these users, subject to the newly imposed secrecy offloading rate constraints and the computation latency constraints, by jointly optimizing their computation and communication resource allocations. We propose an efficient algorithm to solve this problem.

Robust power allocation for two-tier heterogeneous networks under channel uncertainties

In this paper, the trade-off among system sum energy consumption and robustness is studied. In this regard, a robust power allocation problem is formulated for a two-tier heterogeneous network with uplink transmission mode and consideration of imperfect channel state information. The objective is to minimize the total transmit power of femtocell users (FUs), while the interference to macrocell user receiver is limited to a predefined interference level, the transmit power of each FU transmitter is kept within their power budgets, and the actual signal-to-interference-plus-noise ratio of each femtocell receiver is above a minimum threshold. Considering the uncertainties of the interference links from FUs to macrocell base stations and forward transmission links of each FU, the robust power allocation problem is formulated as a semi-infinite programming problem (SIPP). By the worst-case approach, the SIPP is transformed into a convex optimization problem solved by the Lagrange dual decomposition method. Moreover, the feasible regions of constraints, computational complexity, and sensitivity degree of the proposed robust algorithm are also analyzed. Simulation results investigate the impact of channel uncertainties and the superiority of the proposed algorithm by comparing with non-robust algorithm.

BIODIESEL PRODUCTION FROM WASTE FISH FOR ZERO WASTE CONCEPT IN REMOTE AREA OF EASTERN OF JAVA, INDONESIA

Increasing demand fossil fuel in the world may have a good impact on biodiesel demand. Other than produced from plant oil, biodiesel can also be produced from waste fish and fish wastes. Extracted oil from both of fish waste may be turned into biodiesel to be used for ship’s diesel engine or other purposes. The objective of this study is to analyze the energetic efficiency in the production of fish wastes as feedstock for the production of biodiesel in Indonesia. The biodiesel production chain is analyzed to quantify the net yield of energy and exergy and their respective degree of efficiency. The energy consumption calculation for the biodiesel production system is assessed as the sum of energy consumption in different stages in its production chain. Energy efficiency in biodiesel production can be assessed using an index for technical, economic and environmental sustainability analysis. The fish oil was separated from fish wastes using a specially designed oil extraction machine. Both direct and indirect energy and exergy flows are important parameters for evaluating the energetic efficiency of biodiesel. Further, the analysis shows that it is necessary to find ways to improve the exergy efficiency without decreasing the energy efficiency during production of biodiesel from waste fish.

Impact of Air Tightness on the Evaluation of Building Energy Performance in Lithuania

In order to fulfil the European Energy Performance of Buildings Directive (EPBD) requirements for the reduction of energy consumption, European national requirements have been created for building envelope thermal properties and calculation methodology to determine if building energy efficiency is created. This is however not true in all methodologies. The necessity of building air tightness appears only for new A class buildings, and there are no requirements for air tightness for other building classes. Therefore, the aim of this work is to improve the methodology for the calculation of energy efficiency of buildings, while taking into account the air tightness of the buildings. In order to achieve this aim, the sum energy consumption of investigated buildings was calculated, energy efficiency classes were determined, air tightness of the buildings was measured, and reasons for insufficient air tightness were analyzed. Investigation results show that the average value of air tightness of A energy efficiency class buildings is 0.6 h−1. The results of other investigated buildings, corresponding to B and C energy efficiency classes, show insufficient air tightness (the average n50 value is 6 h−1); herewith, energy consumption for heating is higher than calculated, according to the energy efficiency methodology. This paper provides an energy performance evaluation scheme, under which performed evaluation of energy performance of buildings ensures high quality construction work, building durability, and the reliability of heat-loss calculations.

The Influence Factor Analysis of Comprehensive Energy Consumption in Manufacturing Enterprises

This paper conducts the influence factor analysis of comprehensive energy consumption based on a Chinese manufacturing enterprise. By multiple regression analysis, the sum of energy consumption is positive correlation relationship with enterprise scale, and it is negative correlation with enterprise efficiency. Thus, comprehensive energy consumption is main dependent on aggregate output and enterprise performance accordingly. Under a constant aggregate output, enhance energy management and establish the energy management standards are the best approach to promote energy efficiency on manufacturing enterprises. Finally, the limitation and the future direction of this study are discussed.

A futuristic view of energy saving and related energy rebound effect in Bangladesh using complete decomposition model (CDM)

In this paper Complete Decomposition Model is used to compute the future energy saving pattern from the difference of the 'trend' and 'real' values of energy consumption. The 'trend' is defined as a sum of activity effect and the energy use in the base year. The 'real' is defined as a sum of energy consumption in the base year and the change in energy consumption due to the activity effect, structural effect and intensity effect. This analysis is carried out in respect of Bangladesh for the period 2008-2030. The economic sectors that are taken in to account are agriculture, industry and service. The futuristic view shows that Bangladesh can save about 47.47 MTOE in agriculture sector and 34.96 MTOE from service sector. On the other hand, industry sector, which is accounted for 58% of the total energy consumption, failed to save energy, rather the country consumed 227 MTOE more energy than usual. The energy rebound effect that relies upon the activity effect and structural effect has also been estimated to examine the energy uses pattern of these sectors. The aggregate energy rebound effect was found to be 1480 MTOE, of which activity effect and structural effect contribute 91.21% and 8.78% respectively. DOI: http://dx.doi.org/10.3329/bjsir.v47i3.13066 Bangladesh J. Sci. Ind. Res. 47(3), 313-320 2012