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The increasing demand for mobile network capacity driven by Internet of Things (IoT) applications results in the need for understanding better the potential and limitations of 5G networks. Vertical application areas like smart mobility,…

Machine-to-Machine (M2M) communications are one of the major drivers of the cellular network evolution towards 5G systems. One of the key challenges is on how to provide reliability guarantees to each accessing device in a situation in…

In Machine to Machine (M2M) networks, a robust Medium Access Control (MAC) protocol is crucial to enable numerous machine-type devices to concurrently access the channel. Most literatures focus on developing simplex (reservation or…

The rapid deployment of machine learning across platforms from milliwatt-class TinyML devices to large language models has made energy efficiency a primary constraint for sustainable AI. Across these scales, performance and energy are…

Even though machine learning algorithms already play a significant role in data science, many current methods pose unrealistic assumptions on input data. The application of such methods is difficult due to incompatible data formats, or…

Characterizing and predicting the training performance of modern machine learning (ML) workloads on compute systems with compute and communication spread between CPUs, GPUs, and network devices is not only the key to optimization and…

In the coming years, the interconnection of a large number of devices is expected, which will lead to a new form of interaction between the real and the virtual world. In this promising scenario, known as the Internet of Things, it is…

The development of services and the growing demand for resources sharing among users from different organizations with some level of affinity have motivated the creation of Identity Management Systems. Identity Management has gained…

Heterogeneous Networks is the integration of all existing networks under a single environment with an understanding between the functional operations and also includes the ability to make use of multiple broadband transport technologies and…

While the management of heterogeneous network devices is usually solved by protocols like SNMP and NETCONF, there is still no such accepted solution for the management of heterogeneous IoT devices. To avoid the vendor lock-in, several…

Machine-to-machine (M2M) communications have attracted great attention from both academia and industry. In this paper, with recent advances in wireless network virtualization and software-defined networking (SDN), we propose a novel…

The proliferation of resource-constrained devices has become prevalent across various digital applications, including smart homes, smart healthcare, and smart transportation, among others. However, the integration of these devices brings…

A significant increase in the number of interconnected devices and data communication through wireless networks has given rise to various threats, risks and security concerns. Internet of Things (IoT) applications is deployed in almost…

The COVID-19 pandemic and other ongoing health crises have underscored the need for prompt healthcare services worldwide. The traditional healthcare system, centered around hospitals and clinics, has proven inadequate in the face of such…

The review article aims to provide an overview of the challenges and strategies for enhancing interoperability among health information systems in low- and middle- income countries (LMICs). Achieving interoperability in LMICs presents…

Due to massive available spectrum in the millimeter wave (mmWave) bands, cellular systems in these frequencies may provides orders of magnitude greater capacity than networks in conventional lower frequency bands. However, due to high…

Due to the exponential increase in wireless devices and a diversification of network services, unprecedented challenges, such as managing heterogeneous data traffic and massive access demands, have arisen in next-generation wireless…

Tiny Machine Learning (TinyML) is an upsurging research field that proposes to democratize the use of Machine Learning and Deep Learning on highly energy-efficient frugal Microcontroller Units. Considering the general assumption that TinyML…

We study a fundamental problem called Minimum Length Link Scheduling (MLLS) which is crucial to the efficient operations of wireless networks. Given a set of communication links of arbitrary length spread and assume each link has one unit…

As an important part of the Internet-of-Things (IoT), machine-to-machine (M2M) communications have attracted great attention. In this paper, we introduce mobile edge computing (MEC) into virtualized cellular networks with M2M…