Multiple Sinks Research Articles

A quadratically constrained mixed-integer non-linear programming model for multiple sink distributions

Rising traffic congestion and fuel costs pose significant challenges for supply chains with numerous retailers. This paper addresses these challenges by optimizing transportation routes for processed tomatoes within a long-haul and intercity distribution network. We use the heterogeneous capacitated vehicle routing problem framework to create a new quadratically constrained mixed-integer non-linear programming model that aims to meet demand at multiple destinations while minimizing transportation costs. Our model incorporates real-time data and route optimization strategies that consider traffic conditions based on freight time and route diversions for expedited deliveries. It aims to devise an optimal transportation schedule that minimizes fuel, operational, and maintenance costs while ensuring efficient delivery of tomato paste. By applying this model to a real-world case study, we estimate a significant 27.59% reduction in transportation costs, dropping them from GH¢20,270 ($1,638.91) to GH¢14,676 ($1,186.61) on average. This highlights the effectiveness of our strategy in lowering costs while maintaining smooth and efficient deliveries.

Experimental study on a novel self-driven multi-heat sinks system

This article presents a self-driven multi-heat sinks system suitable for cooling multiple heat sources simultaneously. This system can include one driving heat sink and multiple passive heat sinks. The porous medium inside the driving heat sink absorbs heat from its heat source, causing the working fluid to evaporate. The phase changing generating capillary force to drive the circulation of liquid throughout the system. The circulating working fluid flows through the fluid channels in the external passive heat sinks, carrying away the heat from the heat sources at each passive heat sink, thus simultaneously cooling multiple heat sources. This study primarily altered the connections between heat sinks, specifically connecting them in serial and parallel, forming systems with different structures. The operating characteristics of the two differently structured systems were studied through experiments. Results show that both systems effectively dissipate heat, maintaining stable operation at a maximum heat load of 100 W. By comparing the operating characteristics of each heat sink in different structures, it was found that the structure mainly affects the circulation resistance of the working fluid. In the serial system, the high circulation resistance leads to long startup times and high startup temperatures. In contrast, the parallel system effectively addresses these issues and, due to its lower internal circulation resistance, and reduces the operating temperature of the driving heat sink. The parallel system's startup time and temperature are 7% lower than the serial system, and its driving heat sink can handle an additional 10 W of heat load. However, due to the structural impact, each passive heat sink in the parallel system receives lower flow, resulting in higher operating temperatures for the passive heat sinks. Based on the research findings above, the article concludes by outlining the suitable operating conditions for different systems: series-connected and parallel-connected systems are respectively suitable for scenarios where the heat generation of multiple heat sources is similar and where it varies significantly.

On the Reliability of Wireless Sensor Networks with Multiple Sinks.

The convergence of heterogeneous wireless sensor networks provides many benefits, including increased coverage, flexible load balancing capabilities, more efficient use of network resources, and the provision of additional data by different types of sensors, thus leading to improved customer service based on more complete information. However, despite these advances, the challenge of ensuring reliability and survivability remains due to low-cost sensor requirements and the inherent unreliability of the wireless environment. Integrating different sensor networks and unifying protocols naturally leads to the creation of a network with multiple sinks, necessitating the exploration of new approaches to rational reliability assurance. The failure of some sensors does not necessarily lead to a shutdown of the network, since other sensors can duplicate information and deliver data to sinks via an increased number of alternative routes. In this paper, the reliability indicator is defined as the probability that sinks can collect data from a given number of sensors. In this context, a dedicated reliability metric is introduced and examined for its effectiveness. This metric is computed using an algorithm rooted in the modified factoring method. Furthermore, we introduce a heuristic algorithm designed for optimal sink placement in wireless sensor networks to achieve the highest level of network reliability.

Temporally connected components

We discuss a variety of extensions of connected components in temporal graphs, focusing on extensions using connectivity over time through temporal paths (or journeys). Starting with components induced by temporal sources or sinks, we build up to components induced by multiple sources or sinks, and eventually components where all vertices are sources and sinks, i.e. temporally connected components. The cases of bounded components (i.e. defined on time windows), and open or closed components, are also considered. Our contributions mainly include structural results on the number of components, and algorithmic and complexity results of corresponding decision problems. Several new NP-completeness proofs are provided while exploring the boundaries between easy and difficult problems.

Research on heat transfer and flow distribution of parallel-configured microchannel heat sinks for arrayed chip heat dissipation

The heat dissipation ability and compact structure of microchannel flow boiling show great promise for high-efficiency heat dissipation in the field of chip cooling. In arrayed chip cooling scenarios, multiple microchannel heat sinks are typically arranged in parallel. Random fluctuations in the heat load of each chip can lead to non-uniform flow distribution and even thermal failure of the chip. However, there are still limited studies on the non-uniform flow distribution in the parallel use of multiple microchannel heat sinks. This study presents an experimental and theoretical study on the boiling heat transfer and flow distribution characteristics of two heat sinks in parallel using HFE-7100. The steady-state test results indicated that the flow distribution characteristics in parallel-configured heat sinks were closely correlated with the flow pattern. In the single-phase region, flow distribution in both heat sinks was primarily influenced by the physical properties of the fluid. The effect of heat flux on non-uniform flow distribution was within 7 %. When one of the heat sinks entered the two-phase region, microchannel resistance characteristics changed significantly, leading to a dramatic increase in non-uniform flow distribution, up to 26.0 %. The critical heat flux (CHF) was triggered prematurely, with a decrease of up to 31.4 %. In dynamic characteristics testing, when both heat sinks were in the two-phase region simultaneously, the increase in heat flux led to greater non-uniformity in the flow distribution of the parallel-configured heat sinks compared to the single-phase region. Furthermore, considering the transition boundary of two-phase flow patterns in microchannels, a prediction model for flow distribution in parallel-configured microchannel heat sinks was proposed, demonstrating good predictive capability. The research provides a reference for the design and optimization of two-phase cooling systems for arrayed chip configurations.

Stochastic cluster head selection model for energy balancing in IoT enabled heterogeneous WSN

Energy dissipation is the most important design limitation for Internet of Things (IoT) enabled Wireless Sensor Networks (WSNs). In order to prolong the life of WSNs, the energy of nodes must be used in an effective way. Clustering is a strategy that may effectively use the energy of the sensors, extending the life and scalability by managing the network load balance. The energy usage for network operation is reduced by using an evolutionary algorithm called Genetic Algorithm (GA). The Stochastic Cluster Head Selection Model (SCHSM) is described in the proposed protocol by taking the factors such as distance, node energy, density and capacity of nodes for developing the fitness function. The proposed protocol is designed for multiple movable sink nodes and this greatly improves the energy balancing factor in the network. For minimizing the communication gap among sensors and sinks, movable sinks can be placed carefully. Simulation results are analyzed for the system effectiveness.

Comparison of Maximum Heat Transfer Rate of Thin Vapor Chambers with Different Wicks under Multiple Heat Sources and Sinks

In this paper, we present a new analytical model to investigate the maximum heat transfer rate of a thin vapor chamber (TVC) with multiple heat sources and sinks. The model can specifically consider different heat flux conditions for each heat source. Both capillary limitations and allowable maximum temperature constraints were employed to determine the maximum heat transfer rate. The liquid and vapor pressure distributions within the TVC were analytically derived using the Brinkman-extended Darcy equation and the Hagen–Poiseuille equation, respectively. Additionally, the theoretical wall temperature distribution was calculated based on the 3D energy equation, considering different heat flux conditions for multiple heat sources with a weighting factor. Our results demonstrate that the heat flux conditions applied to the heat sources significantly impact the internal flow pattern of the TVC. These changes in flow patterns influence the pressure distributions of the liquid and vapor, thereby affecting the maximum heat transfer rate. Furthermore, the effects of wick parameters on the maximum heat transfer rate under various heat flux conditions were examined.

Industrial Park low-carbon energy system planning framework: Heat pump based energy conjugation between industry and buildings

The accelerating urbanization, rapid industrial development, and excessive consumption of fossil fuels pose survival challenges such as energy depletion and environmental degradation for humanity. In the context of industrial park development, constructing a low-carbon energy system, increasing the proportion of renewable energy, enhancing energy-level matching, and utilizing heat pumps for deep waste heat recovery are effective approaches to reduce fossil energy consumption and alleviate environmental pressures. Addressing issues such as diverse thermal flows in industrial sites, complex electricity-heat-cooling energy demands, and unclear industrial-building energy coupling mechanisms, this paper proposes a two-stage planning framework, comprising the following five steps: (1) constructing a waste heat utilization system centered around heat pumps, (2) establishing a mechanism for matching heat sources, equipment, and thermal sinks, (3) establishing an energy conversion model and energy quality quantification system, (4) optimizing waste heat utilization path allocation, and (5) conducting a system energy flow analysis. Case studies demonstrate that the proposed system achieves optimized matching of multiple heat sources and sinks in industrial and building scenarios through thermal integration, meeting diverse energy demands in the park, including electricity, cooling, and multi-grade heat. After coupling with traditional steam pipeline networks, the annual total cost and annual steam power consumption decrease by 33% and 39% respectively, with a waste heat contribution rate of up to 26% and a renewable energy penetration rate of up to 25%, and a waste heat recovery system payback period of 6 years. By establishing an energy quality quantification system and conducting multi-objective optimization considering losses and economic costs, this paper provides Pareto frontier solutions, offering references for engineering proposals. The proposed networked waste heat recovery system is characterized by low energy consumption and high economic efficiency, effectively integrating the energy characteristics of industrial parks and demonstrating engineering applicability.

Subcooled flow boiling in multiple parallel rectangular micro-channel heat sink: Development of heat transfer correlation

This study experimentally evaluated and presented the heat transfer performance of FC-72 flow boiling in a rectangular micro-channel heat sink under subcooled conditions. The hydraulic diameter of the rectangular micro-channel under investigation is 666 µm, and the heat sink has twenty-four parallel mico-channels machined on an oxygen-free copper block. The width and height of the rectangular micro-channel are 400 µm and 2000 µm, respectively. The experimented mass flux and fluid inlet temperature to the heat sink range between 103–1026 kg/m2s and 20–50℃, respectively. Furthermore, a consolidated subcooled flow boiling database is developed by using the FC-72 flow boiling data of the present experimental study and the subcooled flow boiling database with four different micro-channel heat sinks with HFE-7100 as the coolant by Lee and Mudawar (2008). Nine prominent predictive heat transfer correlations for subcooled flow boiling are methodically assessed and contrasted against the combined database comprising 631 data points. The evaluation resulted in significant variations in the predictions by the correlations with the current consolidated database. The conventional correlations in the literature for flow boiling under subcooled conditions are inadequate for foreseeing the heat transfer during subcooled flow boiling in the micro-channel heat sink as they are developed based on conventional tubes and annuli with channel hydraulic diameters greater than 3 mm. A new subcooled flow boiling heat transfer correlation rooted in dimensionless group terms is then developed from the consolidated database. Compared to prior correlations, better predictive performance is observed for the new subcooled flow boiling correlation against the consolidated database. The newly developed correlation has a mean absolute error of 21.9%, with 74.9% of data points forecasted within ±30%.

Pressure drop correlation for subcooled flow boiling in micro-channel heat sink

This study experimentally explores the subcooled flow boiling pressure drop of FC-72 in a multiple parallel rectangular micro-channel heat sink with a channel hydraulic diameter of 666 µm (width 400 µm and height 2000 µm). Detailed experimental procedures and data reduction methodology are presented. The study analyzes and reports the impact of inlet subcooling on the total pressure drop during subcooled flow boiling of FC-72 in rectangular micro-channels heat sink. Additionally, a consolidated subcooled flow boiling pressure drop database is created by incorporating the additional data points assimilated from the study of Lee and Mudawar (2008), which used HFE-7100 as the coolant fluid. The consolidated database is methodically reviewed and evaluated using the seminal pressure drop correlations described in the literature for pressure drop during subcooled flow boiling. For the micro-channels heat sink adopted in this study, existing subcooled flow boiling pressure drop correlations fail to predict the consolidated database. Based on the consolidated pressure drop data points, a new subcooled flow boiling pressure drop correlation for the rectangular micro-channels heat sink is suggested. The new pressure drop correlation well predicts the consolidated subcooled flow boiling pressure drop database with a mean absolute error of 16.6 % and 86.3 % of data points predicted inside ±30 %.

Carbon storage units and carbon storage obligations: A review of policy approaches

Policies that incentivize the capture and geological storage of CO2 from large point sources (‘CCS’; and more recently, atmospheric removals), have so far tended to reward the resultant avoided CO2 emissions (or CO2 removals) achieved by operators at the point of capture. The expectation has been that geological CO2 storage sites, as well as the connecting infrastructure, will be developed and operated based upon the funding delivered from the single point of incentive (e.g. under an emissions trading system or a carbon tax, only CO2 capture installation operators are absolved of the obligation to acquire and surrender CO2 emission rights or to pay the tax). Project-based crediting mechanisms (e.g. in the voluntary carbon market) tend to treat the entire chain of operations as a single entity to be supplied with emission reduction or removal credits. Consequently, there has been minimal explicit financial incentive to store CO2. Yet a multiple gigaton-per-year scale capture and storage industry requires complex CO2 networks to evolve, with multiple sources connecting to multiple sinks, with installations owned by different operators with different technical expertise, climate mitigation goals and obligations. This multiplicity of goals and incentives can create agency problems and cross-chain risks, which impact negatively upon investment decisions. In this paper, we review the history, evolution and potential of geological net zero (GNZ) and carbon storage (or takeback) obligation concepts applied to fossil carbon producers and suppliers as a means to address these risks alongside policies aimed at atmospheric net zero (ANZ) and fossil carbon emitters.

A Genetic-Algorithm-Based Dynamic Transmission of Data for Communicable Disease in IoMT Environment

Recent advancements in the field of the Internet of medical things (IoMT) have enabled the real-time monitoring and treatment of patients with communicable infectious diseases while minimizing human intervention. However, IoMT devices face challenges such as unbalanced energy consumption, memory constraints, computation power, and low latency, which can deter the efficient transfer of patient monitoring data. Thus, there is an urgent need to establish an energy-efficient infrastructure for IoMT devices to remotely monitor and collect data on communicable diseases. For this, a genetic algorithm (GA) based dynamic transmission of data for communicable diseases in the IoMT environment is proposed in this paper. The energy utilization of the IoMT is enhanced by considering the GA evolutionary processing based on the dynamic sensor range. The proposed work incorporates a periphery of the fixed area for deploying the IoMT devices to settle the energy hole problem. Multiple sinks and direct information collection concepts are also introduced which further improve the performance and reduce the movement of data packets. The proposed protocols not only optimize energy usage but also provide a robust approach for massive data collection and communication.

A novel Asanoha-inspired method for optimal path planning of multiple mobile sinks

A novel Asanoha-inspired method for optimal path planning of multiple mobile sinks

TEAM: A Layered-Cooperation Topology Evolution Algorithm for Multi-Sink Internet of Things

Numerous sensor nodes deployed in the Internet of Things (IoT) can form a large heterogeneous network. The increased energy consumption of sensor nodes and the unbalanced communication load on multiple sink nodes reduce the energy efficiency of the network. Moreover, frequent network attacks also pose severe challenges to topology robustness. Optimizing the network topology to achieve the balance between energy efficiency and robustness is a complex problem. Multi-objective heuristic algorithms based on genetic evolution are commonly used to solve joint optimization problems. However, due to the lack of global search ability caused by the loss of genetic diversity, genetic operations are prone to premature convergence during multi-objective evolution. Therefore, this paper introduces multi-population cooperation into the multi-objective evolution process and proposes a novel layered-cooperation Topology Evolution Algorithm for Multi-sink IoT (TEAM). In TEAM, information entropy is used to measure the effectiveness of load balancing on multiple sink nodes. The crossover and mutation probabilities of different populations are dynamically adjusted to ensure genetic diversity. A layered-cooperation mechanism is designed to avoid premature convergence. Extensive experiments confirm that TEAM can effectively improve the energy efficiency and robustness of network topology while balancing the communication load on multi-sink nodes.

Adaptive squirrel coyote optimization-based secured energy efficient routing technique for large scale WSN with multiple sink nodes

In general, Wireless Sensor Networks (WSNs) require secure routing approaches for delivering the data packets to their sinks or destinations. Most of the WSNs identify particular events in their explicit platforms. However, several WSNs may examine multiple events using numerous sensors in a similar place. Multi-sink and multi-hop WSNs include the ability to offer network efficiency by securing effective data exchanges. The group of nodes in the multi-sink scenario is described through a distance vector. Though, the efficiency of multi-sink WSNs is considerably impacted by the routing of data packets and sink node placement in the cluster. In addition, many WSNs for diverse reasons existed in the similar geographical region. Hence, in this task, a secured energy-efficient routing technique is designed for a Wireless sensor network with Large-scale and multiple sink nodes. Here, the concept of an improved meta-heuristic algorithm termed Adaptive Squirrel Coyote Search Optimization (ASCSO) is implemented for selecting the accurate selection of cluster head. The fitness function regarding residual distance, security risk, energy, delay, trust, and Quality of Service (QoS) is used for rating the optimal solutions. The consumption of energy can be reduced by measuring the mean length along with the cluster head and multiple sink nodes. The latest two heuristic algorithms such as Coyote Optimization Algorithm (COA) and Squirrel Search Algorithm (SSA) are integrated for suggesting a new hybrid heuristic technique. Finally, the offered work is validated and evaluated by comparing it with several optimization algorithms regarding different evaluation metrics between the sensor and sink node.

Towards energy balancing optimization in wireless sensor networks: A novel quantum inspired genetic algorithm based sinks deployment approach

A Wireless Sensor Network (WSN) with multiple sinks alleviates the bottleneck problem of imbalanced energy consumption and leads to improved scalability and convenience in data collection for diverse range of large-scale applications. However, introducing more than one sink also brings a new set of challenges to overcome. To minimize the uneven energy consumption among sensors for longevity of the WSN, it is required to find optimal locations of the sinks that will permit most of the sensors to forward their data using minimum hops and to determine the optimal route for each sink with consistent route length. Routing in large networks is an NP-Hard problem. Previous schemes have solved this problem using multiple sinks deployment either in planned ways or random manner without simultaneously considering the possibilities of network topological changes, edge cases of sensors, and problem of uneven path length. In this context, this paper proposes a quantum inspired genetic algorithm based multiple sinks deployment approach (Q-GEMS) for energy consumption balancing among sensors to extend the network lifetime. Specially, the exiting approaches have focused on either minimizing energy consumption or reducing the path length. In addition to addressing these constraints, the proposed Q-GEMS is designed to be resilient which adapts to any changes in the planned topologies of deployed sinks in anticipation of sensor failures and external influences. Also to achieve greater energy consumption balance among sensors by equalizing the path length and bring down the cost of WSN by minimizing the number of sinks, novel heuristics have been proposed for positioning the sinks, binding the sensors to sinks, evaluating the quality of solutions and updating the Q-bit population. The experimental results show that the proposed Q-GEMS performs comparatively better than state of the art approaches and achieving network lifetime 5.1%, 21%, and 24% longer than that of EEMS, EESS, and DPSO+PSO respectively.

Computational intelligence techniques for energy efficient routing protocols in wireless sensor networks: A critique

AbstractWireless Sensor Networks (WSNs) play a pivotal role in modern data acquisition systems, but their energy‐efficient operation remains a significant challenge. This work provides a concise overview of the key challenges and proposed solutions discussed in the context of energy‐efficient routing protocols for WSNs based on a systematic literature review. The need for fault tolerance to ensure network resilience is vital, given the limited resources and environmental challenges faced by sensor nodes. This work emphasizes the importance of addressing several open research questions, including the integration of diverse topologies, cross‐layer routing, and the use of multiple mobile sinks. Additionally, it highlights the need for QoS‐aware routing for real‐time applications, mathematical modeling for protocol evaluation, and the challenges of testing routing protocols on real hardware. Furthermore, this article suggests leveraging the RPL routing protocol with the Node‐based Metric RNE for enhanced energy efficiency and explores the promising field of hierarchical routing protocols, exemplified by the LEACH protocol and its variants. This work serves as a roadmap for researchers and practitioners, identifying critical challenges and proposing directions for future research to achieve energy‐efficient routing protocols in WSNs, ultimately enabling effective communication in resource‐constrained environments.

Analysis of potential flow networks: Variations in transport time with discrete, continuous, and selfish operation

In potential flow networks, the equilibrium flow rates are usually not proportional to the demands and flow control elements are required to regulate the flow. The control elements can broadly be classified into two types—discrete and continuous. Discrete control elements can have only two operational states: fully open or fully closed. On the other hand, continuous control elements may be operated in any intermediate position in addition to the fully open and fully closed states. Naturally, with their increased flexibility, continuous control elements can provide better network performance, but to what extent?We consider a class of branched networks with a single source and multiple sinks. The potential drop across edges (ΔH) is assumed to be proportional to the nth power of flow rate (Q), i.e., ΔH=kQn , (n≥1). We define R as the ratio of minimal operational times required to transport a given quantum of material with either type of control element and show that 1≤R≤m1−1/n, where m is the maximum depth of the network. The results point to the role of network topology in the variations in operational time. Further analysis reveals that the selfish operation of a network with continuous control valves has the same bounds on the price of anarchy.

Multiple Mobile Sinks for Quality of Service Improvement in Large-Scale Wireless Sensor Networks.

The involvement of wireless sensor networks in large-scale real-time applications is exponentially growing. These applications can range from hazardous area supervision to military applications. In such critical contexts, the simultaneous improvement of the quality of service and the network lifetime represents a big challenge. To meet these requirements, using multiple mobile sinks can be a key solution to accommodate the variations that may affect the network. Recent studies were based on predefined mobility models for sinks and relied on multi-hop routing techniques. Besides, most of these studies focused only on improving energy consumption without considering QoS metrics. In this paper, multiple mobile sinks with random mobile models are used to establish a tradeoff between power consumption and the quality of service. The simulation results show that using hierarchical data routing with random mobile sinks represents an efficient method to balance the distribution of the energy levels of nodes and to reduce the overall power consumption. Moreover, it is proven that the proposed routing methods allow for minimizing the latency of the transmitted data, increasing the reliability, and improving the throughput of the received data compared to recent works, which are based on predefined trajectories of mobile sinks and multi-hop architectures.

Constructal optimization of a rectangular non-uniform heat generation area with irregular high thermal conductivity material

Heat conduction models with three non-uniform heat generation conditions in a rectangular heat generation area (RHGA) are set up in this paper. Under given areas of the irregular high thermal conductivity material (HTCM) and RHGA, constructal optimization of the RHGA is conducted by changing the distribution of the HTCM and aspect ratio of the RHGA. The minimum dimensionless average temperature difference (DATD) of the RHGA is gained. It is found that the DATDs of the RHGA with linear heat generation distribution are abated by 82.43% and 82.65% after twice optimizations for boundary and central heat sinks, respectively. For the heat generation in one local area of the RHGA, the two decrements are 36.30% and 52.20%, respectively. For the heat generation in multiple local areas of the RHGA, the two decrements are 35.60% and 71.60%, respectively. The optimal structure of the RHGA with heat generation in multiple local areas and heat sink in the center exhibits the best cooling performance compared with the other models discussed in this paper. Moreover, the best cooling performance of the RHGA is at least augmented by 29.49% than those of the previous studies discussed in this paper.