Nanonetwork is a new research focus which presents solutions for agricultural, environmental, medical and security fields. Bio-nano hybrid network, which aims to be applied to the human body, is defined as the cooperation of biological units and possible artificial nanomachines. The physical basis of bio-compatible nanonetwork is the intrinsic signal transmission, encoding and decoding in the human body. By studying the communication mechanism, novel nanonetwork could be suggested and further integrated into the standard computer networks. In the meantime, it is also significant for both researchers of experimental biology and computer science to complete a model in cell level, either to provide chances for signal control and recovery in vivo, or to inspire new methods for artificial intelligence. Calcium signaling is a ubiquitous phenomenon in living creatures which takes the responsibility of mediating other messengers and inducing cellular activities. Calcium signaling prevails in astrocyte-a kind of non-electrical cell in the nervous system. Therefore, astrocytes undertake information transmission using calcium waves other than electric pulses. The function of astrocyte in the nervous system has been emphasized in recent years, especially its collaboration with the neurons. Besides, the communication between adjacent astrocytes forms a network with nonidentical intra-network channel efficiency. In addition, given the universal existence of calcium signaling (not exclusive in astrocytes), nano controllers are expected to participate and interfere with the original communication procedure thus leading to signal detection and regulation. This will facilitate disease monitoring and treatment. In this thesis, a conceptual network model is proposed to express the signal transmission from the Peripheral Nervous System to the Central Nervous System. It is divided into four layers: neurons in the Peripheral Nervous System and the spinal cord, neurons in the brain, single astrocyte and groups of astrocytes. The external stimulation is i This dissertation would not have been possible without a lot of people who have helped me and changed my life profoundly during my study at NTU. First and foremost, I would like to express my deepest gratitude to my supervisor, Dr. Yeo Chai Kiat. Her precious and warmest help and care in my research, study and life, infectious enthusiasm, kindness, unlimited patience and inspiring guidance have been the major driving force through my candidature at NTU. Under her supervision and training, I have developed skills in logical thinking, technical writing, communication skills and leadership, which will be invaluable to my future career. Moreover, I would thank the students and staff in CeMNet at the School of Computer Engineering in Nanyang Technological University. I would lke to thank my good friends,