The proliferation of the market in patient care services is attracting attention in the healthcare industry; however, a remote mental healthcare system is still unattainable. In this paper, an ambient intelligent system of in-home psychiatric care service for emergency psychiatry (EM-psychiatry) is proposed for the remote monitoring of psychiatric emergency patients. The emergency psychiatric states of patients are modeled as the states of the maximum-entropy Markov model (MEMM), in which sensor observations, psychiatric screening scores, and patients’ histories are considered as the observations of MEMM. A modified Viterbi, a machine-learning algorithm, is used to generate the most probable psychiatric state sequence based on such observations; then, from the most likely psychiatric state sequence, the emergency psychiatric state is predicted through the proposed algorithm. The ambient EM-psychiatry model is implemented and the performance of the proposed prediction model is analyzed using the receiver operator characteristics curves, which demonstrates that the use of the EM-psychiatric screening questionnaire with biosensor observations enhances the prediction accuracy.

Content Centric Networking (CCN) is one of the most promising network architectures of future Internet. In CCN, Content Router (CR) floods request in the network to find the content. This flooding may degrade the network performance by generating too much traffic. Also, in legacy CCN architecture, each CR caches all contents that pass through it. Thus, same contents are replicated in all CRs along the request path, which incurs faster cache replacement and degrades cache utilization consequently. Furthermore, caching and forwarding decisions are made by the CR only on the basis of its local knowledge, which may not be optimum decisions. In this paper we propose a hybrid caching, cache replacement and requests forwarding approaches to overcome the above drawbacks. In our proposal, there is a virtual controller inside the data center with high performance computational capacity. The controller makes all the forwarding and caching decisions and passes it to the physical CRs via virtualized core router. Physical CRs are grouped inside regions on the basis of their geographical location, in order to enhance users' QoE. We have intensively simulated the proposed mechanism in a chunk level simulator and the performance is compared with existing schemes. The simulation results show that the proposed mechanism outperforms the existing state-of-the-art schemes.

According to increasing performance of mobile devices, like smart phone, tablet PC and etc, and diffusing network infrastructures, like LTE, WiFi and etc, various types of content delivery services based on PC services can serve into mobile devices using cloud. In this paper we proposed content delivery framework with SDN (Software Defined Networking) and CCN (Content Centric Networking) to improve content delivery QoS in mobile cloud environment. Additionally to serve autonomic optimal services, we proposed reinforcement learning based context-aware content delivery scheme. Using our framework, we can guarantee QoS to provide context-aware content delivery scheme.

We exploit helper-to-helper (h-2-h) cooperation using the broadcast nature of wireless sensor networks. The potential helpers overhear the packet from the transmission of previous hop and the helper transmits the packet in the current hop on behalf of the assigned node (sender). We call it friendship relaying cooperative medium access control (FRC-MAC) protocol. This mechanism eliminates the sender transmission phase, improving the energy efficiency and end-2-end delay. Our innovative proposed MAC protocol provides alternate path when a link is poor temporarily, hence no need to find a new path frequently. In this protocol, each node manages a helper queue in additional to its data queue to store cooperative data so that the helper can transmit cooperative data with higher priority than its own data. We performed a simulation study to investigate network performance and compared with existing protocols. We found that FRC-MAC outperforms existing protocols in terms of end-to-end delay and energy efficiency.

Recently smart devices include various interfaces to communicate using 3G, LTE, WiFi and Bluetooth. Additionally a research, named flow mobility, which maintains seamless communication session has progressed using different interfaces in the smart device. Content Centric Network which is one of the Future Internet research issues is studied to solve a problem which is occurred by node mobility. In this paper we propose an efficient and seamless content delivery scheme using flow mobility in CCN. To solve mobility problem in CCN, we introduce a mobility scenario with proposed scheme.

Machine to Machine (M2M), communication between the machines without or with the least-human involvement, is going to be an important part of life. Healthcare is one of the areas on which M2M is going to play major roles. At present time, healthcare sensors monitor patient information and notify remote doctors. However, if we can integrate more intelligence in healthcare sensors, then these can sense patient's emergency condition by themselves and can notify doctor before severe condition. In this context, we have developed intelligent mobile sensor agents in a healthcare scenario in a M2M context. This sensor agent can sense blood pressure of a patient and can notify remote doctor, with the help of an intelligent adapter and a manager in a M2M healthcare scenario.

In this paper, we focus on a scheme that supports mobility for IPv6 over Low power Wireless Personal Area Network (6LoWPAN) sensor nodes. We define a protocol for 6LoWPAN mobile sensor node, named 6LoMSN, based on Proxy Mobile IPv6 (PMIPv6). The conventional PMIPv6 standard supports only single-hop networks and cannot be applied to multihop-based 6LoWPAN. It does not support the mobility of 6LoMSNs and 6LoWPAN gateways, named 6LoGW, cannot detect the PAN attachment of the 6LoMSN. Therefore, we define the movement notification of a 6LoMSN in order to support its mobility in multihop-based 6LoWPAN environments. The attachment of 6LoMSNs reduces signaling costs over the wireless link by using router solicitation (RS) and router advertisement (RA) messages. Performance results show that our proposed scheme can minimize the total signaling costs and handoff latency. Additionally, we present the design and implementation of the 6LoMSN mobility based on PMIPv6 for a healthcare system. According to the experimental results, the 6LoMSN of the proposed PMIPv6-based 6LoWPAN can be expected to use more of the battery lifetime. We also verify that the 6LoMSN can maintain connectivity, even though it has the freedom of being able to move between PANs without a mobility protocol stack.

Content-Centric Network (CCN) sends data to avoid duplicated transmission with content name in the network. However, CCN may cause increase in overhead while maintaining contents management table and create storage problem while storing contents information in the node. In this paper, we proposed a new searching scheme using interesting keyword and manage contents table via overlay network. The content providers with high frequency are chosen in the network. Then an overlay network is constructed using content providers. Via overlay network, it is possible to reduce the number of message transmissions and overhead to manage content management table in the network.

With the penetration of smart-devices and intelligent home-appliances, M2M (machine to machine) communication has opened the door of new prospects for us. The success of such M2M networks depends on its human involvements at the least possible level. In this context, policy based management has huge potentials to be used for M2M communication. This paper presents such a policy based management framework for M2M networks and services. We have considered two M2M communication platforms namely smart-devices and sensor network in our system.