Nguyen Cong Luong

Data Collection and Wireless Communication in Internet of Things (IoT) Using Economic Analysis and Pricing Models: A Survey

This paper provides a state-of-the-art literature review on economic analysis and pricing models for data collection and wireless communication in Internet of Things (IoT). Wireless sensor networks (WSNs) are the main components of IoT which collect data from the environment and transmit the data to the sink nodes. For long service time and low maintenance cost, WSNs require adaptive and robust designs to address many issues, e.g., data collection, topology formation, packet forwarding, resource and power optimization, coverage optimization, efficient task allocation, and security. For these issues, sensors have to make optimal decisions from current capabilities and available strategies to achieve desirable goals. This paper reviews numerous applications of the economic and pricing models, known as intelligent rational decision-making methods, to develop adaptive algorithms and protocols for WSNs. Besides, we survey a variety of pricing strategies in providing incentives for phone users in crowdsensing applications to contribute their sensing data. Furthermore, we consider the use of some pricing models in machine-to-machine (M2M) communication. Finally, we highlight some important open research issues as well as future research directions of applying economic and pricing models to IoT.

Resource Management in Cloud Networking Using Economic Analysis and Pricing Models: A Survey

This paper presents a comprehensive literature review on applications of economic and pricing models for resource management in cloud networking. To achieve sustainable profit advantage, cost reduction, and flexibility in provisioning of cloud resources, resource management in cloud networking requires adaptive and robust designs to address many issues, e.g., resource allocation, bandwidth reservation, request allocation, and workload allocation. Economic and pricing models have received a lot of attention as they can lead to desirable performance in terms of social welfare, fairness, truthfulness, profit, user satisfaction, and resource utilization. This paper reviews applications of the economic and pricing models to develop adaptive algorithms and protocols for resource management in cloud networking. Besides, we survey a variety of incentive mechanisms using the pricing strategies in sharing resources in edge computing. In addition, we consider using pricing models in cloud-based software defined wireless networking. Finally, we highlight important challenges, open issues and future research directions of applying economic and pricing models to cloud networking.

Smart data pricing models for the internet of things: a bundling strategy approach

The Internet of Things (IoT) has emerged as a new paradigm for the future Internet. In IoT, devices are connected to the Internet and thus are a huge data source for numerous applications. In this article, we focus on addressing data management in IoT through using a smart data pricing (SDP) approach. With SDP, data can be managed flexibly and efficiently through intelligent and adaptive incentive mechanisms. Moreover, data is a major source of revenue for providers and partners. We propose a new pricing scheme for IoT service providers to determine the sensing data buying price and IoT service subscription fee offered to sensor owners and service users, respectively. Additionally, we adopt the bundling strategy that allows multiple providers to form a coalition and offer their services as a bundle, attracting more users and achieving higher revenue. Finally, we outline some important open research issues for SDP and IoT.

Mesenchymal Stem Cell Secretome Improves Tendon Cell Viability In Vitro and Tendon-Bone Healing In Vivo When a Tissue Engineering Strategy Is Used in a Rat Model of Chronic Massive Rotator Cuff Tear

Background: Massive rotator cuff tears (MRCTs) represent a major clinical concern, especially when degeneration and chronicity are involved, which highly compromise healing capacity. Purpose: To study the effect of the secretome of mesenchymal stem cells (MSCs) on tendon cells (TCs) followed by the combination of these activated TCs with an electrospun keratin-based scaffold to develop a tissue engineering strategy to improve tendon-bone interface (TBi) healing in a chronic MRCT rat model. Study Design: Controlled laboratory study. Methods: Human TCs (hTCs) cultured with the human MSCs (hMSCs) secretome (as conditioned media [CM]) were combined with keratin electrospun scaffolds and further implanted in a chronic MRCT rat model. Wistar-Han rats (N = 15) were randomly assigned to 1 of 3 groups: untreated lesion (MRCT group, n = 5), lesion treated with a scaffold only (scaffold-only group, n = 5), and lesion treated with a scaffold seeded with hTCs preconditioned with hMSCs-CM (STC_hMSC_CM group, n = 5). After sacrifice, 16 weeks after surgery, the rotator cuff TBi was harvested for histological analysis and biomechanical testing. Results: The hMSCs secretome increased hTCs viability and density in vitro. In vivo, a significant improvement of the tendon maturing score was observed in the STC_hMSC_CM group (mean ± standard error of the mean, 15.6 ± 1.08) compared with the MRCT group (11.0 ± 1.38; P < .05). Biomechanical tests revealed a significant increase in the total elongation to rupture (STC_hMSC_CM, 11.99 ± 3.30 mm; scaffold-only, 9.89 ± 3.47 mm; MRCT, 5.86 ± 3.16 mm; P < .05) as well as a lower stiffness (STC_hMSC_CM, 6.25 ± 1.74 N/mm; scaffold-only, 6.72 ± 1.28 N/mm; MRCT, 11.54 ± 2.99 N/mm; P < .01). Conclusion: The results demonstrated that hMSCs-CM increased hTCs viability and density in vitro. Clear benefits also were observed when these primed cells were integrated into a tissue engineering strategy with an electrospun keratin scaffold, as evidenced by improved histological and biomechanical properties for the STC_hMSC_CM group compared with the MRCT group. Clinical Relevance: This work supports further investigation into the use of MSC secretome for priming TCs toward a more differentiated phenotype, and it promotes the tissue engineering strategy as a promising modality to help improve treatment outcomes for chronic MRCTs.