Efficient energy savings for sensing and mobile systems
Creators: name: ZHANG, Yu
Publisher: name: RMIT University
Year: 2024
Subjects: classificationCode: 460501
subject: Data engineering and data science
classificationCode: 460608
subject: Mobile computing
classificationCode: 460609
subject: Networking and communications

description: Wireless sensor networks (WSNs) have been one of the important milestones towards realizing a pervasive computing infrastructure. Smartphones are also ubiquitous today with an estimated cellular subscription of over 5 billion worldwide. However, no matter what each node in WSNs or smartphones are they remain severely limited by their battery life. This dictates that energy efficiency is important in the context of static and mobile wireless devices. WSNs and smartphone¿s communication have different types of data transfer with different attributes and properties, and consequently, an in-depth study of designing and choosing reliable strategies and approaches to solve the corresponding energy-efficiency problems is of paramount importance.

In this dissertation, we focused on energy savings on two energy constrained target platforms (i.e., static sensor node and mobile smartphone) and approaches. The first part of the dissertation (chapter 2 to 4) covers energy efficient uplink data transmission (i.e. data routing) mechanisms and downlink data transmission (i.e. bulk data or code dissemination) mechanisms to be used on low power sensor nodes (e.g. telosB motes). The approaches adopted are more analytical in nature and evaluations performed in simulation and testbed. The second part of the dissertation (chapter 5 to 7) covers energy efficient mechanism to be used on WiFi smartphone. The techniques proposed improved the power saving mode (PSM) mechanism of the current IEEE 802.11 standard and power control on Mobile Access Points (MAP).

Specifically, in chapter 2, we initially focused on energy balance issues of uplink data transmission in WSNs since most existing works lack theoretical study. The main idea is to divide the network into partitions so that the load of different parts of the network is more even. We conducted comprehensive theoretical analysis to the two-level based mixed data transmission (MDT) scheme when applying to network-wide energy balancing, and eventually to maximize the network lifetime.

In order to better extend tree-based uplink data transmission in WSNs, we identified logical and physical limitations of tree-based transmission to how to exploit the time- variant quality of intermediate link. In chapter 3, we aimed to overcome such limitations by shifting nodal traffic to intermediate links beyond the tree topology. We found that stable performance can be achieved over intermediate links by properly adopting retransmissions. But Low-Power-Listening based MAC may introduce asymmetry issues on intermediate link, leading to redundant transmissions of packets. To overcome the problem, we selected good-SINR links that ensure 95% reliability with at most k retransmissions for communication. We computed the ratio of intermediate-link and tree-link transmissions in a distributed way, aiming at minimizing the maximum load in the neighborhood and finally reducing energy consumption during uplink data transmission.

In chapter 4, since each sensor node needs to quickly receive dissemination data to update local software, nodes have to wake up during the whole reprogramming process. Hence, the time cost is proportional to energy consumption of downlink data transmission or bulk data dissemination. However, the completion time of data dissemination is still lacking theoretical study. We presented a novel high-fidelity analytical model based on the shortest path algorithm to measure the completion time by incorporating overhearing and packet coding. This model can be applied to any coding-based reprogramming protocol by substituting the coding part with protocol specific operations.

Chapter 5 and the next chapter 6, we focused to smartphone's WiFi energy consumption issue (i.e., how PSM can be more efficient by coordinating the transfer of data from AP to mobile devices) from two aspects. The one is for background traffic, the other is for screen-off traffic. For the former, we presented ScaPSM, a design that enables scalable competing background traffic scheduling in crowd event 802.11 deployments. ScaPSM prevents the packet delay proliferation of previous study, if applied in the crowd events scenario, by introducing a new strategy of adequate competition among multiple PSM clients to optimize overall energy saving without degrading packet delay performance. For the latter, we identified energy saving opportunities of Wi-Fi interface emerged during smart- phone's screen-off periods. Exploiting the opportunities, we proposed a new power saving strategy, BackPSM, for screen-off Wi-Fi communications. BackPSM regulates client to send and receive packets in batches and coordinates multiple clients.

In existing system, when WiFi tethering is used, the MAP on smartphone always transmits at the maximum power, this is unnecessary since the mobile device paired to the MAP is often physically nearby and a lower transmission often suffice. In chapter 7, with this observation, we proposed a DATPC scheme to automatically adjust the transmission power of MAP according to the current network condition. A major benefit of this scheme is that not building an accurate energy estimation model but using a preliminary reference, which allows us to eliminate frequent transmission power calculations required in existing power adaptation schemes.

In conclusion, the studies in this thesis aimed to explore measurement, modeling, optimization, intelligence technology and apply them to corresponding solutions to existing WSN uplink data transmission, downlink data dissemination, and smartphone-based WiFi energy efficiency problems. We hope this research will inspire the research community to develop more robust and effective approaches to solve existing problems in this area in the future.