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Disasters are uncertain occasions that can impose a drastic impact on human life and building infrastructures. Information and Communication Technology (ICT) plays a vital role in coping with such situations by enabling and integrating multiple technological resources to develop Disaster Management Systems (DMSs). In this context, a majority of the existing DMSs use networking architectures based upon the Internet Protocol (IP) focusing on location-dependent communications. However, IP-based communications face the limitations of inefficient bandwidth utilization, high processing, data security, and excessive memory intake. To address these issues, Named Data Networking (NDN) has emerged as a promising communication paradigm, which is based on the Information-Centric Networking (ICN) architecture. An NDN is among the self-organizing communication networks that reduces the complexity of networking systems in addition to provide content security. Given this, many NDN-based DMSs have been proposed. The problem with the existing NDN-based DMS is that they use a PULL-based mechanism that ultimately results in higher delay and more energy consumption. In order to cater for time-critical scenarios, emergence-driven network engineering communication and computation models are required. In this paper, a novel DMS is proposed, i.e., Named Data Networking Disaster Management (NDN-DM), where a producer forwards a fire alert message to neighbouring consumers. This makes the nodes converge according to the disaster situation in a more efficient and secure way. Furthermore, we consider a fire scenario in a university campus and mobile nodes in the campus collaborate with each other to manage the fire situation. The proposed framework has been mathematically modeled and formally proved using timed automata-based transition systems and a real-time model checker, respectively. Additionally, the evaluation of the proposed NDM-DM has been performed using NS2. The results prove that the proposed scheme has reduced the end-to-end delay up from 2 % to 10 % and minimized up to 20 % energy consumption, as energy improved from 3 % to 20 % compared with a state-of-the-art NDN-based DMS.

In this paper, we present a joint power allocation and adaptive link selection protocol for an orthogonal frequency division multiplexing (OFDM)-based network consists of one source node i.e., base station (BS), one destination node i.e., (MU) and a buffer aided decode and forward (DF) relay node. Our objective is to maximize the average throughput of the system via power loading over different subcarriers at source and relay nodes. A separate power budget is assumed at each transmitting node to make the system more practical. In order to form our solution more tractable, a decomposition framework is implemented to solve the mixed integer optimization problem. Further, less complex suboptimal approaches have also been presented and simulation results are provided to endorse the efficiency of our designed algorithms.Buffer aided relaying (BAR) emerged as a new paradigm for the wireless communication systems and has provided freedom to the link selection, i.e., the choice to choose a particular hop for transmission in a given time slot [9]. With this addition, the resource allocation problem becomes more challenging and is coupled with the link selection. The optimization techniques designed for memoryless relaying nodes cannot be applied for BAR transmission. Thus, the problem of power allocation and link selection for the BAR has received significant attention in the research community [10][11][12][13][14][15][16][17][18][19][20]. Considering a full-duplex network, power allocation at the source and relay node was studied in [10]. Authors maximized the source arrival rate under the assumption of imperfect self-interference cancellation and statistical delay constraints. For the underlay cognitive radio network with buffer aided DF relay, an adaptive link selection scheme was presented in [11]. A closed-form expression for the data rate was derived by assuming peak power and interference constraints at the secondary nodes. The authors in [12] considered a system where multiple source nodes are communicating with a single destination through a common BAR. Under the total transmit power constraint at each node, this work presented a link selection and a power allocation strategy.The problem of cross-layer resource allocation considering asymmetric time duration over two hops was investigated in [13]. The work in [14] proposed different BAR schemes under full-duplex (FD) relay transmission with self-interference cancellation (SIC) capability at the relaying node. The results showed the considerable gains of the proposed scheme over the conventional FD relay transmission. Further, the authors in [15] studied the security and the delay issues in the buffer enhanced dual-hop transmission. The relay selection schemes for links with equal weights have recently been explored in [16]. Depending on the status of the buffer at each relaying node, the authors in [17] proposed a max-link selection analysis framework. With the Markov chain approach, analytical expressions for the outage probability, the average bit error rate, a...

Nonorthogonal multiple access (NOMA) has been recognized as a key solution to fulfill the demands of 5G wireless communication. In this paper, our aim is to maximize the fairness in the data rates of different users in a multiuser NOMA system. We optimize the downlink transmission subject to minimum rate requirement of each user, limited power budget at the transmitter, and the successive interference cancelation constraint. First, we solve the problem for two‐user scenario where the nonconvex problem is transformed into a standard convex minimization problem and the duality theory is exploited to find the solution. The optimal power allocation is obtained from the Karush‐Kuhn‐Tucker (KKT) conditions, whereas the dual problem is solved via subgradient algorithm. As a next step, we consider the general multiuser optimization problem where more than two users can share the same channel under NOMA transmission. We design efficient solution techniques to solve the nonconvex optimization problem with sequential quadratic programming (SQP). Furthermore, two suboptimal low complexity solutions are also presented. We found that, under the proposed schemes, the fairness increases with increasing the available transmit power and decreases with the increasing the number of users. We show a complexity comparison of the dual‐based solution and the SQP algorithm. It is observed that power optimization through KKT conditions exhibits much lower computational complexity as compared to the SQP‐based solution.