Sleeping Schedule-Aware Local Broadcast in Wireless Sensor Networks

Abstract

Broadcast is widely used in applications in wireless sensor networks (WSNs). In the last decade, the broadcast problem in WSNs has been well studied. However, few of existing broadcasting strategies have considered the scenarios with sleeping schedules, which have been emerging as a prevalent energy-saving method for WSNs. In WSNs with sleeping schedule, each node switches on and off periodically, rendering the broadcast problem more difficult. To handle the periodical sleep issue, we focus on designing effective sleeping schedule-aware broadcast algorithms. We practically propose SALB, a sleeping schedule-aware local broadcast algorithm. In SALB, a typical local algorithm for constructing connected dominating set is employed to form the broadcast backbone. To guarantee proper transmission of broadcast messages, a sleep-aware forwarding mechanism is implemented. Moreover, heuristic strategies are used to decrease the number of transmissions and the broadcast latency. Theoretical analysis shows that the number of transmissions for SALB is within 4(min(Δ,| |) + ) ( is constant) is constant) times of the optimal value. And the broadcast latency of SALB is within 4| | + 1 times of the optimal value (Δ is the maximum degree in the network, | | is the scheduling period length). The performance of SALB is evaluated via simulations.

The Energy Complexity of Broadcast

“…In this work we presented what we believe are the first theoretical results on the energy complexity of problems in multi-hop networks. It is interesting that many of the techniques we used (lots of sleeping, tightly scheduled transceiver usage, 2-hop neighborhood coloring) are somewhat similar to techniques suggested in systems papers [36,38,37,16,17], but without rigorous asymptotic guarantees.…”

“…In [1, Section 9.1], idle listening (i.e., a device is active, but no message is received) and packet collisions are identified as major causes of energy loss. An approach to this issue is to adaptively set the work/sleep cycle of the devices [36,38,37]; based on this approach, practical energy-efficient algorithms for Broadcast have been designed [16,17]. Another route to reducing the energy cost is via Time Division Multiple Access (TDMA) algorithms, which reduce collisions by properly assigning time slots to the devices [15,24].…”

Delay-sensitive flooding based on expected path quality in low duty-cycled wireless sensor networks

“…Let one flooding round to be the time from when the source node starts to send out the flooding packet, until the packet reaches every node. Energy consumption of node i in one flooding round is the summation of energy for transmitting, receiving, listening (being active without transmitting/receiving), and sleeping as in equation (10) in which E t , E r , E l , and E s are the energy spent of a node for transmitting, receiving, listening, or sleeping per time slot, respectively. The n t i , n r i , n l i , and n s i stand for the number of time slots in one flooding round that the node is in the four states mentioned above.…”

“…One possible way to prolong network life span is to run sensors in low duty-cycled mode. [8][9][10] As the name suggests, nodes in duty cycle mode periodically switch between active and sleeping states. Each sensor node is active for just a short period of time (time slot), and rest of the time, it stays in sleeping state (turning off the radio).…”

UAV-Assisted Low-Consumption Time Synchronization Utilizing Cross-Technology Communication

“…Therefore, time synchronization operations are required to achieve time consistency between nodes. Accurate time synchronization can save communication energy, promote position accuracy, optimize monitoring range, and improve system security [ 7 , 8 , 9 , 10 , 11 ]. Previous research in this field mostly focused on how to do time synchronization for better clock accuracy, such as reference broadcast synchronization (RBS) [ 12 , 13 ], timing-sync protocol for sensor networks (TPSN) [ 14 , 15 ], and flooding time synchronization protocol (FTSP) [ 16 , 17 , 18 , 19 ].…”