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A major area of application of multiobjective path problems and resolution algorithms is telecommunication network routing design, taking into account the extremely rapid technological and service evolutions. The need for explicit consideration of heterogeneous Quality of Service metrics makes it advantageous for the development of routing models where various technical–economic aspects, often conflicting, should be tackled. Our work is focused on multiobjective path problem formulations and resolution methods and their applications to routing methods. We review basic concepts and present main formulations of multiobjective path problems, considering different types of objective functions. We outline the different types of resolution methods for these problems, including a classification and overview of relevant algorithms concerning different types of problems. Afterwards, we outline background concepts on routing models and present an overview of selected papers considered as representative of different types of applications of multiobjective path problem formulations and algorithms. A broad characterization of major types of path problems relevant in this context is shown regarding the overview of contributions in different technological and architectural network environments. Finally, we outline research trends in this area, in relation to recent technological evolutions in communication networks. [ABSTRACT FROM AUTHOR]

A major area of application of multiobjective path problems and resolution algorithms is telecommunication network routing design, taking into account the extremely rapid technological and service evolutions. The need for explicit consideration of heterogeneous Quality of Service metrics makes it advantageous for the development of routing models where various technical–economic aspects, often conflicting, should be tackled. Our work is focused on multiobjective path problem formulations and resolution methods and their applications to routing methods. We review basic concepts and present main formulations of multiobjective path problems, considering different types of objective functions. We outline the different types of resolution methods for these problems, including a classification and overview of relevant algorithms concerning different types of problems. Afterwards, we outline background concepts on routing models and present an overview of selected papers considered as representative of different types of applications of multiobjective path problem formulations and algorithms. A broad characterization of major types of path problems relevant in this context is shown regarding the overview of contributions in different technological and architectural network environments. Finally, we outline research trends in this area, in relation to recent technological evolutions in communication networks.

Abstract Internet of Things (IoTs) as a new network pattern for the intelligent world usually uses wireless sensor networks (WSNs) as a perception layer which consisted of numerous number of sensor nodes scattered in the environment to gather intended information. The selected information then is sent to a base station (BS) to be sent to cloud server for further processing. Since the energy of sensor nodes is limited, the most significant challenge in these networks is reducing the energy consumption of the network. It is proved that dividing the network to clusters can significantly reduce the energy consumption. One of the most popular clustering protocols in WSNs is the Low‐Energy Adaptive Clustering Hierarchy (LEACH). In this protocol, cluster heads (CHs) are selected randomly which results in poor performance in real scenarios. In this article, a new energy aware CH selection algorithm is proposed which selects CHs based on the residual energy, the position and centrality of nodes. It uses a variable range upon which the centrality and the number of neighbours of each node are calculated. Simulation results show that the proposed algorithm outperforms LEACH, Multi‐hope Routing with LEACH (MR‐LEACH) and Enhanced Multi‐hop LEACH (EM‐LEACH) in terms of reducing energy consumption, increasing network lifetime and improving network reliability.

Abstract Due to characteristics of high bandwidth and low latency, datacenter networks ensure tremendous data could be transmitted in an efficient way. However, in many‐to‐one transmission scenarios, high concurrency of TCP flows aggravates network congestion and causes overflows in switches, seriously impairing network performance. To solve the problem, a TCP congestion control mechanism based on software‐defined networking (STCC) is proposed. Without any modification in TCP stack, STCC monitors network performance through centralized control and global network view of SDN, employs a routing algorithm based on the minimum path bandwidth utilization rate to forward packets and uses different methods to adjust congestion windows of senders so that network congestion can be greatly mitigated. An experiment platform is built to carry out simulation tests for evaluating STCC, and the results show that under the same network conditions, STCC effectively reduces the number of retransmission timeout of senders and noticeably raises network throughput, compared with other congestion control algorithms.

Abstract The elastic optical network (EON) is the latest solution to increase the capacity of optical networks, as a response to the ever‐increasing demand for traffic. To meet the EON mission, new algorithms and frameworks need to be designed. In this paper, a new algorithm based on EON is proposed that employs a subtree‐based scheme to establish multicast transmissions. To solve the problems of routing, modulation level and spectrum allocation, the primary problem of EON with regard to resource allocation under wavelength continuity and wavelength contiguity constraints, as well as distance adaptive transmission, the proposed algorithm solves each subproblem by considering the existence of a solution for other subproblems. The authors take into account the effects of splitting the transient light at the intermediary nodes on the signal‐to‐noise ratio to enhance the accuracy of the resource allocation. The proposed scheme is extensively examined under different networks and compared with the existing multicasting benchmark. The simulation results show that the proposed scheme considerably increases the network capacity without placing any burden on the network.

The existence of link correlation has been empirically validated, and different exemplary works exploit the link correlation in the designing of various network protocols. In this work, the authors investigated the impact of this link correlation in contention mechanism of medium access control (MAC). They illustrated negative link correlation could deteriorate the contention mechanism designed to handle hidden terminal problems and, consequently, increase the packet collision rate between the neighbours. They also showed that negative link correlation could increase the chance of an exposed terminal problem. Therefore, ignoring negative link correlation could lead to overestimate overall network throughput and underestimate packet delay. Next, instead of designing a new contention mechanism exploiting the link correlation, they proposed a new routing tree which mitigates the negative effect of negative link correlation without altering the underlying MAC layer. They evaluated this routing tree on Indriya testbed with TelosB nodes and compared it to the minimum spanning tree based on link quality only. The results show improvement in end‐to‐end throughput and packet reception ratio at each node. [ABSTRACT FROM AUTHOR]

The existence of link correlation has been empirically validated, and different exemplary works exploit the link correlation in the designing of various network protocols. In this work, the authors investigated the impact of this link correlation in contention mechanism of medium access control (MAC). They illustrated negative link correlation could deteriorate the contention mechanism designed to handle hidden terminal problems and, consequently, increase the packet collision rate between the neighbours. They also showed that negative link correlation could increase the chance of an exposed terminal problem. Therefore, ignoring negative link correlation could lead to overestimate overall network throughput and underestimate packet delay. Next, instead of designing a new contention mechanism exploiting the link correlation, they proposed a new routing tree which mitigates the negative effect of negative link correlation without altering the underlying MAC layer. They evaluated this routing tree on Indriya testbed with TelosB nodes and compared it to the minimum spanning tree based on link quality only. The results show improvement in end‐to‐end throughput and packet reception ratio at each node. [ABSTRACT FROM AUTHOR]

A communication void is one of the most serious issues in any routing techniques. This issue occurs when a node does not have any forwarder node to forward the data packets towards the sink node or surface station. The presence of a void node affects the overall performance of routing techniques in terms of end‐to‐end delay, data loss, energy consumption, and so on. The primary objective of this work is to avoid the void region in underwater sensor networks (UWSNs). For the same purpose, this work introduces the void‐hole avoidance routing algorithm for UWSNs. This work avoids horizontal transmission, which further reduces the end‐to‐end delay. The residual energy, depth, holding time, and distance from the sending node to the forwarding node and forwarding node to the surface station are used as a matrix to select the best forwarder node. The simulation has been done on MATLAB to analyse the performance of the proposed algorithm. The proposed routing algorithm attained better performance using the metrics, namely packet delivery delay, number of dead nodes, and energy tax with the values of 0.9147, 48, and 72.14 by varying the transmission range, and 0.9184, 38, and 71.12 by varying the network size, respectively. [ABSTRACT FROM AUTHOR]

The objective of this work is the calibration of a generalised cost function for the bicycle network links to be used in conjunction with assignment methods for uncongested networks, as cyclists are generally much less delayed by traffic congestions with respect to auto‐traffic. The calibration's goal is to find a coefficient vector for a linear link‐cost function that maximises the overlap between routes obtained with a minimum cost routing of cyclists' demand and the relative cyclists' chosen routes, identified by a map‐matching procedure of recorded global positioning system (GPS) traces. The calibration focuses on minimising an objective function through different established evolution‐based optimisation algorithms, thus avoiding the generation of route choice sets. Link cost functions are calibrated for a modified Openstreet network of Bologna, Italy, using GPS data from the European cycling challenge and Bella Mossa campaign. Results show an improvement of up to 30% of overlapping routes with respect to pure distance‐based routing. It is also demonstrated that the calibrated link‐costs are transferable to a different scenario. [ABSTRACT FROM AUTHOR]

In past few years, wireless sensor network (WSN) is considered as an essential and imperative way for efficient data communication in ubiquitous computing environment along with the fulfilment of objectives such as (i) lifetime enhancement and (ii) energy conservation. Till date, the research findings demonstrate that clustering of WSNs is an effective and pertinent approach. Moreover, designing of energy‐aware routing schemes for clustered WSNs is a basic necessity due to resource‐restricted nature of these sensor nodes. This study has a twofold contribution. First, the research dimensions of WSNs are explained by incorporating recent work carried out as per findings in real scenarios. Secondly, this study presents a comprehensive survey of existing clustering schemes for WSNs based on metaheuristic techniques. This study is beneficial for researchers of this domain as it surveys the literature over the period 2000–2020 on energy efficiency in clustered WSNs. [ABSTRACT FROM AUTHOR]

The clustering technique is a key routing method for large‐scale wireless sensor networks (WSNs), which strongly extends the network's lifetime and scalability. The fundamental protocol of this technique, which is called low energy adaptive clustering hierarchy (LEACH), is proved as a solution that offers good energy efficiency and consequently expands the network lifetime. As the energy efficiency is deteriorated with the network size, LEACH improvements are becoming so substantial to support the scalability in the large‐scale WSNs. The authors propose a new dynamic multi‐hop clustering protocol. It exploits both the mobility and the multi‐hop communication to prolong the lifetime of the mobile WSN. The proposed protocol, called dynamic multi‐hop LEACH (DMH‐LEACH), combines the dynamic clustering, multi‐hop transmissions, and node mobility to improve the energy efficiency of LEACH. They also study the effect of the traffic and energy heterogeneity on the proposed protocol. Finally, they simulate DMH‐LEACH protocol for both homogeneous and heterogeneous scenarios. The simulation results show that the proposed protocol allows to better balance the energy consumption for all sensor nodes and considerably extends the network's lifetime. [ABSTRACT FROM AUTHOR]

Logic expressions can be designed from actin filaments. It is a protein that makes the cellular structure and plays an important role in intracellular communication. Nano communication technique has been established using actin cellular automata. Among several rules, (1, 30) and (4, 27) rules have been used to design 2 to 1 multiplexer, 4 to 1 multiplexer, 1 to 2 demultiplexer and 1 to 4 demultiplexer. Router or data selector has been made of using multiplexer and demultiplexer. Three novel circuits such as multiplexer, demultiplexer and nano‐router have been designed using the projected mechanism. The primary focus of this proposed technique is on different designs of the multiplexer, demultiplexer and minimum cell count with minimum time steps. The different router circuits have been simulated with the help of Simulink by which output has been verified for different circuits. Stuck at fault analysis is also done in this study. Device density and power consumption have also been included in this study. A comparative analysis of the different designs of the router provides a better concept of circuit optimisation. Furthermore, this study analyses convenient forthcoming applications in nano‐technology and nano‐bio‐molecular systems involving the proposed parameters. [ABSTRACT FROM AUTHOR]

To solve the inefficient use of internet protocol (IP) addresses in the current host‐centric internet, the content‐centric networking (CCN) replaces the IP address with the content name and the cache memory is used to store data temporarily on each router. One of the key components in CCN is the pending interest table (PIT). When an interest arrives at a CCN node, the node searches the PIT entries for the same request. If no, the node searches the PIT for an idle entry and a request is sent. If there is no idle entry, the request is blocked. If yes, the aggregation mechanism is performed. To prevent the request from becoming out‐of‐date, the timeout mechanism is adopted. In this work, the authors focus on the performance analysis of PIT in the cellular network with two classes of interests, new and handoff interests. To provide service differentiation, a reservation mechanism is adopted. Furthermore, interests may enter the retrial queue and wait to retry later. First, the authors derived the analytical model for the system considered. Second, the impact of various system parameters on the performance measures is studied. Last but not least, computer simulation is written to verify the accuracy of the analytical results. [ABSTRACT FROM AUTHOR]

Advances in processor, memory, and radio technology will enable small and cheap nodes capable of sensing, communication, and computation. Networks of such nodes can coordinate to perform distributed sensing of environmental phenomena. In this paper, we explore the directed-diffusion paradigm for such coordination. Directed diffusion is data-centric in that all communication is for named data. All nodes in a directed-diffusion-based network are application aware. This enables diffusion to achieve energy savings by selecting empirically good paths and by caching and processing data in-network (e.g., data aggregation). We explore and evaluate the use of directed diffusion for a simple remote-surveillance sensor network analytically and experimentally. Our evaluation indicates that directed diffusion can achieve significant energy savings and can outperform idealized traditional schemes (e.g., omniscient multicast) under the investigated scenarios.

For the operation of the spinning frame in the spinning mill, Hall sensors are used to test the running rate of each axis of the spinning frame. In order to centrally monitor the operation of the spinning frame, analyse the production site environment, communication distance and node layout, ZigBee is used to establish a networked monitoring system to improve the stability of rate acquisition and enhance the stability of data transmission. According to the actual condition at the production site, the ZigBee traditional routing algorithm is improved to be more convenient and efficient in the textile mill environment and have the packet loss rate reduced. The rate collection node sends the collected data to the coordinator. The coordinator uploads the data to the upper computer by WI-FI module through WI-FI gateway. The results show that the improved routing algorithm greatly reduces the packet loss rate and the entire monitoring system is stable and reliable.

For the operation of the spinning frame in the spinning mill, Hall sensors are used to test the running rate of each axis of the spinning frame. In order to centrally monitor the operation of the spinning frame, analyse the production site environment, communication distance and node layout, ZigBee is used to establish a networked monitoring system to improve the stability of rate acquisition and enhance the stability of data transmission. According to the actual condition at the production site, the ZigBee traditional routing algorithm is improved to be more convenient and efficient in the textile mill environment and have the packet loss rate reduced. The rate collection node sends the collected data to the coordinator. The coordinator uploads the data to the upper computer by WI-FI module through WI-FI gateway. The results show that the improved routing algorithm greatly reduces the packet loss rate and the entire monitoring system is stable and reliable. [ABSTRACT FROM AUTHOR]

With emerging programmable network architectures gaining momentum in the networking industry, it is necessary to look at how the services currently offered on traditional network architectures can be fully migrated to the programmable networks. In traditional networks, lightpaths are used for providing high‐bandwidth consuming services that are usually sensitive to delay. Lightpath scheduling requires admission control mechanisms, routing and wavelength assignment algorithms, and protection and restoration mechanisms that ensure reliable and efficient lightpath routing. Software defined networking (SDN) is the emerging programmable network architecture that paves the way for easier network management and configuration by using application programming interfaces. The state‐of‐the‐art in lightpath routing for wavelength division multiplexing networks focusing on lightpath scheduling, routing, protection and restoration in optical software defined networks is surveyed. Moreover, open research issues for SDN lightpath routing solution are discussed. [ABSTRACT FROM AUTHOR]

Owing to the limited network resources in ad hoc networks, improving network throughput is the key to solve network congestion and increase network transmission efficiency. Back‐pressure routeing, as an optimal routeing strategy for throughput, has recently received substantial attention for joint routeing and scheduling over multi‐hop wireless networks. However, the inefficient routeing decision and complex queueing management of back‐pressure routeing make it unsuitable for practical applications. This study proposes an improved back‐pressure routeing algorithm with one first‐input–first‐output (FIFO) queueing structure using the shortest‐path decision. By making use of the shortest‐path knowledge, the feasible routes quickly converge to the shortest path when the network is lightly loaded. On the other hand, when the network load is heavy, the proposed algorithm remains optimal for exploring all the feasible paths between each source and destination. The back‐pressure routeing design based on a single‐FIFO queue architecture greatly simplifies the complexity of packet queueing management. The authors' results indicate that the proposed routeing algorithm achieves lower end‐to‐end delay than that of some other back‐pressure algorithms without reducing the network throughput performance. [ABSTRACT FROM AUTHOR]

Routeing protocol for low‐power and lossy networks (RPL) are widely used in dynamic wireless sensor network. Several types of researches worked on RPL and designed hybrid energy‐efficient cluster‐parent‐based RPL, queue utilisation (QU)‐RPL, improved RPL, attack detection RPL etc. to support from vulnerable threats, provide efficient routeing and balance dynamic nodes in the network. Previous research findings dealt with certain limitations and problems. In this study, a new coordinative‐balanced clustering algorithm is proposed which is enabled to balance destination‐oriented directed acyclic graph (DODAG) that is formed in each cluster. Pruning of nodes from DODAG effectively maintains cluster with minimised complexity. This study also resolves the problem of two common security attacks such as distributed denial of service attack (DDoS) and version number attack. Then, enriched‐ant colony optimisation is used for DDoS detection and a secure route is chosen to perform data transmission. At the instance of selecting best parent for forwarding data, the authors use residual energy and scoring factor. Scoring factor of each node denotes the legitimacy to be selected as the best parent. Finally, results obtained from Network Simulator 3 indicate better performances on the following metrics: packet delivery ratio, end‐to‐end delay, node death minimisation, packet loss rate and power consumption. [ABSTRACT FROM AUTHOR]

Selection strategy is an essential part of an adaptive routing algorithm that influences the performance of the networks‐on‐chip (NoC). A selection strategy is used for selecting the best output channel from the available channels according to the network status. This study presents a new output selection strategy called destination intensity and congestion aware (DICA) that uses both local and regional congestion information from adjacent and two hops away neighbours on the path to destination based on the channel and switch information. Also, the proposed output selection strategy uses a new global congestion‐aware scheme based on destination node called destination congestion awareness method to distribute traffic more equally over the network. The simulation results show that DICA strategy consistently improves the performance in both throughput and average latency with minimal overhead in terms of area consumption for various synthetic and real application traffic patterns. In addition, the microarchitecture of NoC routers is also presented in this study and it shows that the proposed output selection strategy can be combined with any adaptive routing algorithms. The experimental results show the average delay improvements of DICA to the Bufferlevel, neighbours‐on‐path, and regional congestion awareness are 87, 57, and 24%, respectively. [ABSTRACT FROM AUTHOR]

The comparative analysis of the active queue management (AQM) has been seen in the past work, while the comparative analyses for combined multiple output responses or performance parameters viz., throughput, delay, and loss rate are rarely seen in the literature. The comparative analysis using single variable comprising the output performance parameters has been attempted. The sensitivity of the network parameters over the throughput, delay, and loss rate for different AQM schemes has been measured. An attempt has also been made to stabilise the AQM algorithm that aims to achieve a low‐loss rate and a high throughput. The models for the stabilisation of queue size of random early detection (RED) based on the network parameter maxp have been studied. The comparative performance analysis of existing stabilised models has also been presented with author's modified RED. The key idea is to modify the existing RED algorithm to achieve stabilisation in queue length at routers with the reduced loss rate as compared to RED. [ABSTRACT FROM AUTHOR]

Mobile ad hoc networks (MANETs) are attractive for many applications because of their easy‐to‐use and self‐organising nature. However, the routing overhead problem has always been a bottleneck restricting the development of MANETs technology. The reason behind is the traditional blind flooding methods and frequent route initiations caused by node mobility. Reducing routing overhead has a huge impact on saving energy consumption of mobile nodes and improving the MANETs performance. In this study, a distributed dynamic routing algorithm is proposed to establish an efficient routing mechanism for MANETs. Based on the mobility of nodes, a fuzzy positional relationship between nodes is constructed. Using this relationship, an improved routing method is designed. The authors characterise this relationship between nodes and implement the proposed algorithm in an ad hoc routing architecture. The simulation results show that the proposed routing algorithm achieves good performance in reducing routing overhead and improves the efficiency of packet transmissions in MANETs. [ABSTRACT FROM AUTHOR]

The 3D geographic routing in mobile wireless sensor networks (MWSNs) is gaining importance because of its simplicity, effectiveness, scalability and low cost. This study proposes a 3D geographic routing for multimedia traffic in MWSNs where the node which captures/senses an event establishes the route to the sink. If distance of an event node (source node) to the sink is within the sensing range, then the event data is transmitted to the sink. Otherwise, event node broadcasts bandwidth requirement to nodes. The surrounding nodes reply with bandwidth availability which is computed using fuzzy inference system situated in the node. The reply also comprises of node's residual energy and its distance to the sink. Event node identifies neighbour nodes which can provide the required bandwidth. The event node then selects the forwarder node from the list of neighbour nodes based on their residual energy and distance to the sink using another fuzzy inference system. The selected forwarder node becomes the source node and the process is repeated until one of the forwarder node finds the sink as neighbour. The algorithm is compared with dynamic 3D fuzzy routing based on traffic probability algorithm and novel fuzzy clustering scheme to demonstrate the improved performance. [ABSTRACT FROM AUTHOR]

This study proposes a routing algorithm to enhance throughput and spectrum utilisation efficiency for underwater cognitive acoustic sensor networks (UCASNs). In a UCASN, each cognitive acoustic (CA) user would sense the medium to detect available spectrum resources. However, CA users have no exact knowledge about the communication mechanism of the primary users (PUs) such as sonar users or sonar interference sources. In addition, because of the frequency‐dependent attenuation, the available frequencies in water are severely limited and are still underutilised. Therefore, by analysing the behaviour of the CA users based on the ON–OFF process in the primary channel, an optimisation problem is derived to maximising the spectrum utilisation taking into account the bandwidth requirement of CA users. In this way, an efficient routing algorithm for UCASNs is proposed to enable throughput improvement of the network while reducing interference to PUs. Finally, simulation results are shown to verify the effectiveness of the authors proposed scheme. [ABSTRACT FROM AUTHOR]

With the rapid implementation and expansion of the Internet of things (IoT) technologies in smart cities, network congestion control and energy‐efficient routing in wireless sensor and actuator networks (WSANs) for virtualising IoT have emerged as a crucial area of research in recent years. This study implements the particle swarm optimisation (PSO) algorithm to realise network congestion control and energy‐efficient routing in the transport layer of WSANs. This algorithm is based on the flocking behaviour of birds. The simulation results show that the proposed PSO‐based approach provides better performance in terms of network lifetime and packet drop ratio compared with the ant colony optimisation and the artificial bee colony algorithm. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) does not stop integrating an important number of components and objects that are characterised by their complexity and heterogeneity. Such constraints make the existing routing protocols unsuitable for IoT communications in a smart cities environment. To accomplish all the expected tasks and satisfy the user services, it is important to guarantee a quality of communication that answers to the requirements of smart cities applications in terms of data and processing. This study addresses the problem of the performance degradation of IoT communications in smart cities and proposes a new routing algorithm to improve them. The proposed algorithm is called SSRA (smart and self‐organised routing algorithm), which can select the best route for the packets. SSRA allows a self‐organising routing process according to a new situation of the network and devices parameters recently detected. When using SSRA, the communication records an improvement in performance in terms of packet delivery rate, throughput, end‐to‐end delay and overhead packets. SSRA extends also the devices lifetime by allowing fair and efficient energy consumption. [ABSTRACT FROM AUTHOR]

Sensors with IoT assistance provides secured communication and data integrity inside HAN. Energy reading and information flow from the smart grid, together with sensors, bring about a new perspective on energy management. This paper primarily investigates the secured data flow in HAN and assures data privacy of customers during critical and emergency operations. Data are made available in real time with minimum transit time delay. Devices are continuously monitored for vital and emergency services. This paper focuses on machine to machine data flow and packet delivery using IoT. It helps in making user's power consumption data available over the cloud and also in customised electronic devices in real‐time. This research work showcases the requirements for developing a cost‐effective IoT‐HAN connected with smart grid for energy aware routing. The advanced design scheme helps to place sensors, and control gateway in a well‐defined boundary, consuming less energy for data transfer and data processing. Data flow pattern and packet delivery rate is tested using both simulated and actual data from sensors and concentrators. The obtained results and flow pattern is evaluated using MATLAB and network simulator. The developed IoT‐HAN setup is optimally helpful in secured data exchange among different connected devices inside HAN. [ABSTRACT FROM AUTHOR]

Deep packet inspection (DPI) acts as a tool to control and classify incoming network traffic depending on users,content, applications and becomes a very important aspect of every network today. Instead of utilising only incoming packet header information, Internet service providers utilise DPI for security purposes, flow management, and routing. The high‐performance challenges that face DPI techniques to manage line‐speed packet processing with restricted available memory are the increasing traffic volumes and link rates. Bloom (BF) and quotient (QF) filters are effective randomised data structures for performing approximate membership queries. They have been employed in many networking applications including DPI. Nevertheless, they consume more calculations which degrade the system performance. Consequently, in this paper, the authors propose a new variant of membership query data structure, called quotient‐based Cuckoo filter (QCF), that reflects a merging process between QF and CF to minimise the calculation overhead and employing it in a DPI system. QCF employs only two hash functions and consumes less calculation overhead than BF, QF, and CF. The implementation results show that using QCF as an identification tool in a DPI system result in a time improvement up to 77% over CF and up to 98% over BF and QF. [ABSTRACT FROM AUTHOR]

This study presents a new placement and routing method for analogue integrated circuit layout generation based on an evolutionary algorithm, which is called modified cuckoo optimisation algorithm. Layout parasitic effects are taken into account to ensure that the performance of the circuit is not deteriorated. In order to verify the performance of the proposed method, layouts of three different circuits including differential to single‐ended amplification stage, two‐stage and three‐stage operational amplifiers (op‐amps) are automatically generated in a 0.18 μm CMOS process with a 1.8 V supply voltage. The simulation results show the efficiency of the proposed algorithm in the analog layout generation. [ABSTRACT FROM AUTHOR]

This study attempts to deduce the optimal hops in a multi‐hop wireless sensor network (WSN) ensuring power‐efficient communication under signal‐to‐interference noise ratio (SINR) constraints. The authors model the total route power consumption under wireless channel quality constraints. WSNs usually employ a multiple‐source, single‐sink structure for information transfer, necessitating data aggregation. The authors calculate optimal hops for three different data aggregation schemes. They further propose a robust hybrid data aggregation strategy that demonstrates an improved performance with respect to minimal power consumption when compared with employing individual data aggregation schemes. The data aggregation scheme employing optimal hops has been implemented and results have been verified for an illustrative application in water supply and drainage monitoring system. The authors have formulated the problem as a standard convex optimisation problem. They employ Karush–Kuhn–Tucker optimality conditions to derive the analytical expressions of the globally optimal hops, which incorporate the influence of route power, receiver noise, and SINR thresholds. The transmit power and hop count are varied simultaneously until an optimised hop count is achieved. The relation between the node transmit power and the number of hops in the route is derived and the condition for feasible optimal hops is presented. [ABSTRACT FROM AUTHOR]

Nowadays, it is important to evaluate the use of IPv6 wireless networks. Indeed, the implementation of IPv6 mechanisms and features must be examined. IPv6 requires many objects exchanges like IPv6 routing information which could be communicated by different messages multicast. These messages are too frequent; they could impact energy consumption related to battery‐powered objects. Therefore, the energy consumption is nowadays, one of the most important issues in small object networks with IPv6. Thus, the aim of this study is to suggest a new algorithm called minimising energy consumption under connectivity constraint. The performance evaluation is based on several parameters that would help in maintaining connectivity between the mobile objects and their default router. The results showed that energy consumption could be minimised by optimising IPv6 multicast messages. Overall, this method results a significant effectiveness and might be used as a future wireless networks improvements. [ABSTRACT FROM AUTHOR]

Efficient algorithms for solving the routing and spectrum assignment (RSA) problem in flex‐grid optical networks are of paramount importance to leverage network efficiency. Exact approaches based on integer linear programming (ILP) models are known to be computationally hard and hence, difficult to solve for realistic models while heuristics have inherent downsize of local optimal trapping. In addressing those issues, this paper firstly presents a novel and efficient heuristic based on the genetic algorithm (GA) to provide (near‐) optimal solutions to the RSA problem. The effectiveness of the GA‐based algorithm is benchmarked against typically used reference heuristics for a set of network scenarios and it is shown that in addition to the better performance than conventional heuristics in the literature, the proposed GA technique indeed could achieve optimal solutions in most cases while the running time is still manageable. Secondly, we propose to make use of efficient solutions from the heuristic approaches to set the upper‐bound and warm‐start point for ILP formulation. This combination has been shown very productive in enhancing running time performance and increasing the capability of achieving an optimal solution and/or improving the solution quality in a given time span compared with traditional ways for solving ILP models. [ABSTRACT FROM AUTHOR]

The sensor nodes of wireless sensor networks (WSNs) are usually positioned in remote or inaccessible areas and hence the physical maintenance such as battery replacement is more difficult. One of the core challenges of WSN is to increase the network life time, meaning that the efficiency of power utilisation should be the maximum. The major reasons for high power consumption are drawn out transmission path to reach sink, work load add‐ons on nodes closer to storage medium, and the energy necessary for storage. This study proposes a novel method of data storage and retrieval for WSN environment to improve the network lifetime by minimising the energy consumption. The proposed method accomplishes this milestone using four novel algorithms, namely weighted optimum storage‐node placement(SNP), efficient and energetic wireless recharging, efficient rule‐based node rotation and critical‐state‐data passing. The areas of influence of this proposed method are SNP, wireless recharging, node rotation and cooperative multi‐input–multi‐output clustering/routing. Simulation results claim that the proposed method multiplies the WSN topology lifetime ratio by a significant level and outperforms the earlier versions significantly. [ABSTRACT FROM AUTHOR]

In opportunistic networks (OppNets), routing and data forwarding among mobile devices are facilitated by relays or next‐hop forwarders. To guarantee end‐to‐end data delivery it is important to provide participation. However, in sparsely connected OppNets, it is extremely challenging to monitor the behaviour of the relays and identify selfish/malicious relays cooperating with each other in order to forge routing information or drop useful data. Cooperation enforcement schemes are seen as a lightweight alternative to conventional secure forwarding techniques that involve cryptographically signed certificate exchanges, providing a 'softer' security layer to protect basic networking operations. In general, cooperation enforcement schemes fall into two broad categories: trust establishment via a reputation system and pricing or credit‐based schemes. This study offers a comprehensive survey of representative cooperation enforcement schemes that exploit a reputation system. The authors analyse their distinct features, identify and discuss critical challenges that should be efficiently addressed when designing such mechanisms, indicating at the same time potential solutions and provide an informative table to display the authors' findings. From this analysis, they examine issues and concerns surrounding the field of cooperation enforcement in OppNets, and provide guidelines and directions for future researchers. [ABSTRACT FROM AUTHOR]

Most of researches on wireless sensor network (WSN) are focused on how to reduce energy consumption to increase the network lifetime. There are few researches solving the problem of energy optimization ensuring delay constraint. Whereas, the delay is important factor for applications that require delay‐sensitive data. Several works have been published to balance the energy consumption and delay. They achieved many different results but each proposal has certain limitations. Some proposals have high computational and messaging complexity. Some others have not found the optimal solution. In this study, we investigate in finding solution to improve the energy efficiency of sensor nodes satisfying end‐to‐end delay to transmit data from sensor nodes to sink in multi‐hop WSNs. Based on Lagrange relaxation method, we propose an aggregate cost function between energy consumption and delay as well as an efficient method to find the optimal multiplier for that objective function. We provide two algorithms to find paths with least energy consumption while maintaining end‐to‐end delay requirement from any sensor node to sink. Besides analyzing the complexity and convergence of the algorithm, the simulation results also show that the proposed algorithm achieved good balance between energy consumption and delay compared with the previous proposals. [ABSTRACT FROM AUTHOR]

Transmission power control is an effective method to reduce energy consumption for wireless sensor networks. However, the current algorithms of power control have relatively low accuracy. At the same time, the parameters cannot be adjusted dynamically. In order to improve the energy utilisation as well as data transmission efficiency and balance the load, therefore, a fuzzy power‐optimised clustering routing algorithm is proposed in this study. The algorithm optimises the iteration radius and classifies the sensor nodes into different categories according to their node degree. Then select the cluster head by multi‐parameter iteration adaptively among the same category, and optimise the cluster structure with a comprehensive consideration of parameters such as degree of centralisation, distance between node and base station and so on. Finally, fuzzy control is used to adjust the transmission power of cluster nodes dynamically to minimise the energy consumption. Simulation results show that when the average cluster radius RL=60, weight of election parameters α=0.2, adjustment parameter of cluster radius η=0.7, compared with other similar algorithms, the proposed algorithm prolongs the lifetime by at least 42.2% and increases the amount of data packets by at least 40.1%. [ABSTRACT FROM AUTHOR]

With the huge growth of the Internet of Things (IoT) in manufacturing, agricultural and numerous other applications, connectivity solutions have become increasingly important especially for those covering wide remote area in the scale of kilometre squares. Although many low‐power wide‐area network (LPWAN) technologies such as Long Range are supposed to support long‐range low‐power wireless communication, the underneath star topology limits the scalability of the networks due to the need of a central hub. To provide connectivity to a wider area, the authors propose to build the mesh topology upon these LPWAN technologies. One of the challenges of meshing these networks is the routing mechanism originally designed for star networks is not energy sensitive. In this Letter, the authors address this issue by proposing a distributed as well as energy‐efficient reinforcement learning based routing algorithm for the wide area wireless mesh IoT networks. They evaluate the failure rate, spectrum and power efficiencies of the proposed algorithm by simulations, which resemble the long‐range IoT networks, by comparing it to that of a random routing with loop‐detection algorithm and a centralised pre‐programmed routing algorithm which represents the ideal scenario. They also present a progressive study to demonstrate how the learning in the algorithm reduces the power consumption of the entire network. [ABSTRACT FROM AUTHOR]

In this study the authors are interested in safety-critical real-time applications implemented on distributed architectures supporting the time-sensitive networking (TSN) standard. The on-going standardisation of TSN is an IEEE effort to bring deterministic real-time capabilities into the IEEE 802.1 Ethernet standard supporting safety-critical systems and guaranteed quality-of-service. TSN will support time-triggered (TT) communication based on schedule tables, audio-video-bridging (AVB) flows with bounded end-to-end latency as well as best-effort messages. The authors first present a survey of research related to the optimisation of distributed cyber-physical systems using real-time Ethernet for communication. Then, the authors formulate two novel optimisation problems related to the scheduling and routing of TT and AVB traffic in TSN. Thus, the authors consider that they know the topology of the network as well as the set of TT and AVB flows. The authors are interested to determine the routing of both TT and AVB flows as well as the scheduling of the TT flows such that all frames are schedulable and the AVB worst-case end-to-end delay is minimised. The authors have proposed an integer linear programming formulation for the scheduling problem and a greedy randomised adaptive search procedure-based heuristic for the routing problem. The proposed approaches have been evaluated using several test cases.

Distance adaptive spectrum allocation exploits the tradeoff between spectrum width and reach to improve resource utilisation by tailoring the modulation format to the level of impairments along the path. The authors first show that the distance‐adaptive routing and spectrum assignment (DA‐RSA) problem is a special case of a multiprocessor scheduling problem. The authors then develop a suite of efficient and effective DA‐RSA algorithms for ring networks, that build upon list scheduling concepts. This work explores the tradeoffs involved in DA‐RSA algorithm design, and opens up new research directions that may leverage the vast literature in scheduling theory. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) consist of spatially distributed sensor nodes to monitor physical or environmental conditions. These sensor nodes are typically battery‐powered sensor nodes (BPSNs) and can rarely meet design goals of long network lifetime and high reliability. Energy‐harvesting sensor nodes (EHSNs) that convert different types of energy to electrical energy are an alternative type of sensor nodes with a long lifetime but a high cost. Combining BPSNs and EHSNs has potential to deal with the conflicting design goals of long lifetime and reasonably low cost. In this study, the authors make new contributions by modelling a heterogeneous WSN consisting of both BPSNs and EHSNs and proposing a comprehensive cost function‐based routing approach that integrates end‐to‐end path reliability, cost and energy consumption for providing satisfactory quality of service to applications running on hybrid WSNs. Another contribution made in this work is the optimal deployment of EHSNs using a reliability‐importance‐analysis‐based method to improve the end‐to‐end path reliability within hybrid WSNs. [ABSTRACT FROM AUTHOR]