The development of new technological applications is driving the need for deterministic network communication that exhibits reliable behavior. This is particularly relevant for applications like automation and autonomous vehicles, which require real-time network responsiveness. This has led to the development of various technologies, including Time-Sensitive Networking (TSN). Recent studies have explored the optimization of scheduling and routing in TSN, as this is crucial for meeting TSN’s objectives. Current methods primarily focus on scheduling Time-Triggered (TT) transmissions, often overlooking the scheduling of lower-priority traffic types. Many of these methods do not optimize routing, and only a few consider reliability. In this paper, we present the Optimized Hybrid Deterministic Scheduling and Routing Plus (OHDSR+) approach. This method prioritizes communications, optimizing both scheduling and routing of TT communications, while also addressing the requirements of lower-priority best-effort (BE) communications, and ensuring the reliability of TT communications. We evaluated our approach using various problem instances. The results demonstrate our approach’s effectiveness in managing different traffic types and ensuring reliable transmission for TT traffic. Our model achieves significant improvements compared to the state-of-the-art REU-CP-R method, with reductions in total latency of up to 1.03%, total response time of up to 34.70%, and scheduling response time of up to 63.97%. Notably, OHDSR+ exhibits superior scalability, successfully finding solutions for all tested network sizes with a 100% success rate, while REU-CP-R achieved only an 87.5% success rate. This highlights OHDSR+’s ability to provide optimal solutions for networks of various sizes with minimal latency and response times.

Real-time communications characterized by low-latency, deterministic, and reliable behavior are crucial for the advancement of emerging technologies. Consequently, Time-Sensitive Networking (TSN) has been developed to address the distinct demands of sectors such as automation and autonomous vehicles applications. This is currently achieved through various methods that emphasize the scheduling of critical data traffic. However, many of these methods determine routes independently, potentially impacting the schedulability of transmissions. Additionally, there is a noticeable lack of emphasis on the scheduling and routing of low-priority transmissions within TSN. In this paper, we introduce the optimized hybrid deterministic scheduling and routing (OHDSR) approach. This method takes into account the priority of communications to jointly optimize the scheduling and routing of time-triggered (TT) communications, while also catering to low-priority best-effort (BE) communications. Extensive experimental evaluations show the high efficiency of our proposed method. It ensures not only the prompt delivery of TT communications but also the delivery of BE communications within suitable time frames, with a maximum difference of 14.29% from TT communications, meeting their respective deadlines. Moreover, the evaluation demonstrates the high scalability of the proposed approach, providing improved response times compared to the latest work for both routing and scheduling.

CQI-MCS Mapping for Green LTE Downlink Transmission

Massive multiple-input multiple-output (m-MIMO) is considered as an essential technique to meet the high data rate requirements of future sixth generation (6G) wireless communications networks. The vast majority of m-MIMO research has assumed that the channels are uncorrelated. However, this assumption seems highly idealistic. Therefore, this study investigates the m-MIMO performance when the channels are correlated and the base station employs different antenna array topologies, namely the uniform linear array (ULA) and uniform rectangular array (URA). In addition, this study develops analyses of the mean square error (MSE) and the regularized zero-forcing (RZF) precoder under imperfect channel state information (CSI) and a realistic physical channel model. To this end, the MSE minimization and the spectral efficiency (SE) maximization are investigated. The results show that the SE is significantly degraded using the URA topology even when the RZF precoder is used. This is because the level of interference is significantly increased in the highly correlated channels even though the MSE is considerably minimized. This implies that using a URA topology with relatively high channel correlations would not be beneficial to the SE unless an interference management scheme is exploited.

The software-defined network (SDN) is a new technology that separates the control plane from data ‎plane for the network devices. One of the most significant issues in the video ‎surveillance system is the link failure. When the path failure occurs, the monitoring center cannot receive the ‎video from the cameras. In this paper, two methods are proposed to solve this problem. The first ‎method uses the Dijkstra algorithm to re-find the path at the source node switch. The second method ‎uses the Dijkstra algorithm to re-find the path at the ingress node switch (or failed link). Based on ‎simulation results, it is concluded that the second method consumes less time (lower transmission delay) than the first method. The delay consumed by the second method is half the delay in the first method. Also, the packet loss rate for second method is 14%, while 16% in the first method. The jitter for second method is almost similar to the jitter without link fail. Therefore, ‎the second method led to select the path with small losses without impact on video quality. ‎Finally, the results of two methods are compared in terms of end to end delay, packet loss rate, and jitter.‎  

Nowadays, datacenters become more complicated and handle many more users’ requests. Custom protocols are becoming more demanded, and an advanced load balancer to distribute the requests among servers is essential to serve the users quickly and efficiently. P4 introduced a new way to manipulate all packet headers. Therefore, by making use of the P4 ability to decapsulate the transport layer header, a new algorithm of load balancing is proposed. The algorithm has three main parts. First, a TCP/UDP separation is used to separate the flows based on the network layer information about the used protocol in the transport layer. Second, a flow size prediction technique is adopted, which relies on the service port number of the transport layer. Lastly, a probing system is considered to detect and solve the failure of the link and server. The proposed load balancer enhances response time of both resources usage and packet processing of the datacenter. Also, our load balancer improves link failure detection by developing a custom probing protocol.