Recently, named data networking (NDN) has been proposed as a promising architecture for future Internet technologies. NDN is an extension to the content-centric network (CCN) and is expected to support various applications in vehicular communications [vehicular NDN (VNDN)]. VNDN basically relies on naming the content rather than using end-to-end device names. In VNDN, a vehicle broadcasts an “Interest” packet for the required “content,” regardless of end-to-end connectivity with servers or other vehicles and known as a “consumer.” In response, a vehicle with the content replies to the Interest packet with a “Data” packet and named as a “provider.” However, the simple VNDN architecture faces several challenges such as consumer/provider mobility and Interest/Data packet(s) forwarding. In VNDN, for the most part, the Data packet is sent along the reverse path of the related Interest packet. However, there is no extensive simulated reference available in the literature to support this argument. In this paper, therefore, we first analyze the propagation behavior of Interest and Data packets in the vehicular ad hoc network (VANET) environment through extensive simulations. Second, we propose the “CODIE” scheme to control the Data flooding/broadcast storm in the naïve VNDN. The main idea is to allow the consumer vehicle to start hop counter in Interest packet. Upon receiving this Interest by any potential provider, a data dissemination limit (DDL) value stores the number of hops and a data packet needs to travel back. Simulation results show that CODIE forwards fewer copies of data packets processed (CDPP) while achieving similar interest satisfaction rate (ISR), as compared with the naïve VNDN. In addition, we also found that CODIE also minimizes the overall interest satisfaction delay (ISD), respectively.

Smart cities have been envisioned during the last decade. Moreover, various projects have been initiated to bring this concept into reality. Smart city is basically an emergence of the existing and new Information and Communications Technologies (ICT) to make our living standard more safe and digitized. Wireless communications, such as sensors, actuators, intelligent transportation systems, and smart grids, have played a vital role in the dissemination of information under the given circumstances. Similarly, it is hard to declare any city as a smart city without taking benefits from wireless sensor networks (WSNs). However, with new requirements and delay sensitive applications, the existing WSN requires significant alterations at several layers. In this paper, a new time division multiple access (TDMA)-based medium access control (MAC) protocol, called bitmap-assisted efficient and scalable TDMA-based MAC (BEST-MAC), is proposed for adaptive traffic in hierarchical WSNs that can be deployed in the smart cities. BEST-MAC is specifically designed to improve the quality control of such smart cities applications, where diverse traffic is required and loss or delay in data traffic is unacceptable. The main contributions of BEST-MAC include: 1) it uses small size time slots; 2) the number of those time slots is more than the number of member nodes; 3) knapsack algorithm is used to schedule time slots; and 4) short node address (1 B) is proposed to identify the member nodes. First two contributions of BEST-MAC handle adaptive traffic loads of all members in an efficient manner. The knapsack algorithm not only reduces the job completion time of a node but also minimizes the average packet delay with better link utilization. The short node address reduces the control overhead that improves the energy efficiency. The simulation results verify that the proposed BEST-MAC transmits more data with less delay and energy consumption compared with the existing MAC protocols.

In this paper, we propose an adaptive time division multiple access based medium access control (MAC) protocol, called bitmap-assisted shortest job first based MAC (BS-MAC), for hierarchical wireless sensor networks (WSNs). The main contribution of BS-MAC is that: (a) It uses small size time slots. (b) The number of those time slots is more than the number of member nodes. (c) Shortest job first (SJF) algorithm to schedule time slots. (d) Short node address (1 byte) to identify members nodes. First two contributions of BS-MAC handle adaptive traffic loads of all members in an efficient manner. The SJF algorithm reduces node's job completion time and to minimize the average packet delay of nodes. The short node address reduces the control overhead and makes the proposed scheme an energy efficient. The simulation results verify that the proposed BS-MAC transmits more data with less delay and energy consumption compared to the existing MAC protocols.

Vehicular named data network (VNDN) has emerged as a promising network technology, where the focus of communication is moved from host-centric to information-centric. Since, the VNDN is at its early stage in development, there are several open issues to be explored and pending interest table (PIT) management is one of them. In VNDN, PIT stores each broadcasted interest until the required content is retrieved or its timer (PEL: PIT entry lifetime) expires. When the PIT storage is full, the vehicles discard new incoming interests, thus decreasing the network performance. Therefore, in this letter, we propose a dynamic PEL (DPEL) scheme that enables each relaying vehicle to dynamically compute PEL timer for each incoming interest using its interest satisfaction rate (ISR) and the hop count. The higher the ISR and the longer the hop count, the shorter the time the relaying vehicle keeps the PIT entry. Simulation results show DPEL reduces by more than 75% the PEL and the number of entries in VNDN.

The Smart Grid, a fusion of digital technologies and advanced communication methods, enables the transformation of power distribution, transmission, and generation by responding to fluctuations in electricity consumption. Conventional electrical grids often leave consumers unaware of their energy usage patterns, resulting in both energy wastage and financial loss. To enhance energy efficiency, the consumption patterns of consumers need regulation. Smart Grids efficiently employs Demand-Side Management (DSM) strategies, including peak clipping, load shifting, and consumer awareness campaigns, to optimize energy consumption and achieve energy savings. DSM’s synergy with smart meters and smart energy management systems (SEMS) emerges as a powerful trio in comprehensive energy conservation and optimization. The integration of SEMS with the Internet of Things (IoT), augmented by the advancements in 5G technology, emerges as a transformative paradigm. SEMS, operating within the IoT ecosystem bolstered by 5G connectivity, facilitates the instantaneous and efficient integration of IoT in SEMS, enabling real-time data collection, in-depth analysis, and data-driven decisions for optimal energy management. This empowers users with the ability to make data-driven decisions, yielding tangible outcomes in the form of efficacy, cost reductions, and fortified sustainability initiatives. We present a SEMS that amalgamates three microcontroller units to create a smart meter that is further integrated with a cloud-based middleware module and consumer API. Furthermore, it collects vital power metrics such as voltage, current, kWh, kW, and PF. Consumers can conveniently access this data in real-time via an API. Energy service companies can leverage this data for incentive programs and to motivate customers to optimize their energy consumption. These datasets serve as a foundational element for the development of diverse DSM strategies. This research work presents the deployment, and performance evaluation of an IoT-based SEMS that is implemented in diverse settings, including industrial, commercial, building, and warehouse setups. Moreover, as a test case, our evaluation extends to the specific conservation of energy within air-conditioning systems. The SEMS achieves significant energy conservation, with calculated savings ranging from 5% to 53%, showcasing its effectiveness in targeted energy management. The real-time data and case studies further demonstrate the efficiency of the presented work.

Named Data Networking (NDN) has been recently added to the future Internet family. NDN is basically an extension to the Content Centric Network (CCN) and is expected to support various applications. Those applications are to be supported by the future internet architectures. NDN believes in naming the content rather than using end-to-end device names. Recently, NDN has been adapted into Vehicular Ad hoc Networks (VANETs) and hence, we name it Vehicular NDN (VNDN). At it's early stage, VNDN faces several challenges such as consumer/provider mobility, Interest/Data forwarding, content caching and so on. Mostly, VNDN relies on the fact that Data is sent back to the consumer via same path the Interest packet was received from. However, we analyzed that it's not true in a VANET and there is lack of discussion about managing the Data flow back to the consumers in the current literature of VNDN. In this paper, we therefore, pursue to control the data flooding/broadcast storm of the conventional VNDN by proposing our scheme “CONET”. The main idea of CONET is to allow the consumer vehicle to start hop counter in the Interest message and upon receiving that interest by any potential provider, to include Time To Live (TTL) value with data messages. The TTL value includes the number of hops, Data packets should travel on its way back to the consumer. Simulation results show that CONET forwards less Copies of Data Messages Processed (CDMP) while achieving similar Interest Satisfaction Rate (ISR) as the basic VNDN. In addition, CONET also minimizes the overall Interest Satisfaction Delay (ISD), respectively.