Abstract
Suboptimal algorithms for planning a sequence of information messages in the communication network of mobile autonomous participants are proposed. The algorithms use as optimality criteria the upper bounds of either the total delivery time of all messages from the transmitted sequence or the average delivery time over the messages. Several formulations of the problem are considered, which differ in the presence or absence of preliminary ordering for the set of messages.
Similar content being viewed by others
REFERENCES
I. A. Kalyaev, A. R. Gaiduk, and S. G. Kapustyan, Models and Algorithms of Collective Control in Groups of Robots (Fizmatlit, Moscow, 2009) [in Russian].
C. Amato, G. D. Konidaris, G. Cruz, C. A. Maynor, J. P. How, and L. P. Kaelbling, “Planning for decentralized control of multiple robots under uncertainty,” in Proceedings of the IEEE International Conference on Robotics and Automation, Washington, DC, 2015, pp. 1214–1248.
K. S. Amelin, N. O. Amelina, and O. N. Granichin, “Adaptive multi-agent real-time operating system for UAV complexes,” in Actual Problems of Russian Cosmonautics, Proceedings of the 38th Academic Readings (Komiss. RAN, Moscow, 2014), p. 654.
A. V. Inzartsev, L. V. Kiselev, V. V. Kostenko, et al., Underwater Robotic Systems: Systems, Technologies, Applications (Dal’nauka, Vladivostok, 2018) [in Russian].
G. Giger, M. Kandemir, and J. Dzielski, “Graphical mission specification and partitioning for unmanned underwater vehicles,” J. Software 3 (7), 42–54 (2008).
V. P. Fedosov, S. P. Tarasov, P. P. Pivnev, et al., Communication Networks for Underwater Autonomous Robotic Systems (YuFU, Taganrog, 2018) [in Russian].
F. S. Pankratov and I. M. Malakhov, “Actual and perspective methods of constructing wireless access networks in underwater acoustic communication,” Upravl. Bol’sh. Sist., No. 91, 120–143 (2021).
A. Hamilton, S. Holdcroft, D. Fenucci, P. Mitchell, N. Morozs, A. Munafo, and J. Sitbon, “Adaptable underwater networks: The relation between autonomy and communications,” Remote Sens. 12 (2020).
I. E. Tufanov and A. F. Shcherbatyuk, “Some marine trial results of centralized control system for marine robot group,” Upravl. Bol’sh. Sist., No. 59, 233–246 (2016).
K. G. Kebkal, A. I. Mashoshin, and N. V. Moroz, “Solutions for underwater communication and positioning network development,” Girosk. Navig. 27 (2), 106–135 (2019).
L. Kleinrock, Queueing Systems (Wiley-Interscience, New York, 1975).
G. Tel, Introduction to Distributed Algorithms (Cambridge Univ. Press, Cambridge, 1994).
R. V. Konvei, V. L. Maksvell, and L. V. Miller, Schedule Theory (Nauka, Moscow, 1975) [in Russian].
Yu. E. Malashenko, I. A. Nazarova, and N. M. Novikova, “Analysis of two-layer resource supply flow networks,” J. Comput. Syst. Sci. Int. 59, 387 (2020).
A. A. Lazarev and E. R. Gafarov, Schedule Theory. Tasks and Algorithms (Mosk. Gos. Univ., Moscow, 2011) [in Russian].
J. W. S. Liu, Real-Time Systems (Prentice-Hall, Englewood Cliffs, NJ, 2000).
F. Cottet, J. Kaiser, and Z. Mammeri, Scheduling in Real-Time Systems (Wiley, New York, 2002).
G. H. Hardi, J. E. Littlewood, and G. Pólya, Inequalities, Cambridge Mathematical Library (Cambridge Univ. Press, Cambridge, 1988).
Funding
The work was supported by the Russian Science Foundation, grant no. 22-29-00339.
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
The authors declare that they have no conflicts interest.
APPENDIX
APPENDIX
Proof of Statement 1. We transform expression (2.1):
It is easy to see that in this expression only the first sum depends on the ordering of the messages, which means that only it is subject to minimization:
Let us expand this expression
It is known that the sum of pairwise products of members of two numerical sequences has a minimum value if one of these sequences increases and the other decreases [18]. Since the coefficients (n – k) decrease with increasing k, then the minimum average delivery time is reached only when \({{e}_{{[k]}}}\) increase with increasing k or at least do not decrease.
Proof of Statement 2. We assume the opposite, namely that the order of the queue π minimizes the upper bound \(\hat {\Delta }_{s}^{w}\), but the statement condition is not satisfied for it, i.e., there is such a position l that
Let L and \(L{\kern 1pt} '\) be the numbers of messages in the queue π in positions l and l + 1. Let us form a queue \(\pi {\kern 1pt} '\), swapping around messages L and \(L{\kern 1pt} '\) in the queue π. Delivery of the first l – 1 and last \({{n}_{i}} - l - 1\) messages are completed in both queues at the same time. As a result, these messages contribute equally to the weighted sum in (2.3). Thus, the difference in the value of criterion (2.3) for two variants of queues π and \(\pi {\kern 1pt} '\) determined by the terms for messages L and \(L{\kern 1pt} '\). Let
Then for π
For \(\pi {\kern 1pt} '\)
We compare for queues π and \(\pi {\kern 1pt} '\) the values of the total contributions of the criteria of the studied messages L and \(L{\kern 1pt} '\). It is easy to see that for π the contribution contains \({{w}_{{L{\kern 1pt} '}}}{{e}_{L}}\) but does not contain \({{w}_{L}}{{e}_{{L{\kern 1pt} '}}}\) and vice versa. However, from (A.1) it follows that \({{w}_{{L{\kern 1pt} '}}}{{e}_{L}} \geqslant {{w}_{L}}{{e}_{{L{\kern 1pt} '}}}\). This implies that the value of criterion (2.3) for π is more than for \(\pi {\kern 1pt} '\) and that the assumption that this ordering minimizes the upper bound \(\hat {\Delta }_{s}^{w}\) is incorrect. Thus, the statement being proved is true.
Proof of Statement 3. We denote by \({{\hat {\Delta }}_{{g[k]}}}\) the upper bound of the delivery time for a group of messages that is among the groups at the k-th position. Then the upper bound of the total delivery time of all groups is determined by the expression
Let us rewrite it by analogy with (2.1)
where \({{\bar {\delta }}_{{g[k]}}}\) is the upper bound for the time interval from the moment emission is completed to the moment of delivery of all messages from the group located at the k-th position. In this expression, the second and third sums representing the total duration of the group and the interval \({{\bar {\delta }}_{{g[k]}}}\) are constant. Moreover, the first (double) sum depends on the order of the groups. Applying an analysis similar to that used in the proof of Statement 1, we conclude that the groups in the plan must be ordered in accordance with (2.4).
Proof of Statement 4. Let us write an expression for the upper bound on the delivery time of the j-th message of the group located at the k-th position:
where \({{\bar {\delta }}_{{[k],j}}}\) is the upper bound of the time interval from the moment of completion of emission of the j-th message of the group located at the k-th position, until the delivery of all messages in this group is completed.
Let us analyze the expression for the upper bound of the average message delivery time over the entire queue:
We transform this expression using the relation (A.3)
In this expression, the second term is a constant value that does not depend on the order of the groups. The first term does not depend on j and therefore transforms to the form
From a comparison of this expression, for example, with expression (2.3), the validity of this statement follows.
Proof of Statement 5. The idea of the proof is based on the fact that the distinguished subgroups can be considered as the groups from the previous statement, i.e., although they can be interrupted, it is proved that this interruption does not improve the plan.
We consider the subgroup b of some group formed in accordance with the statement algorithm and containing nb messages. Let
If you designate a message in the subgroup b of the pair (b, j), where j is the sequence number of the message in the subgroup, then the subgroup is given by the sequence (b, 1), …, (b, \({{n}_{b}}\)). Breaking a subgroup means splitting it into two parts \(b{\kern 1pt} '\) and \(b{\kern 1pt} ''\):
Each of these new parts of the subgroup has its own conditional upper bound on the delivery time
which, in accordance with Statement 4, would determine the place of the parts of the subgroup in the plan.
We need to prove that such partitioning of the subgroup b is inappropriate because part \(b{\kern 1pt} '\) must immediately precede \(b{\kern 1pt} ''\), and the structure remains unchanged.
Let us show that
Inequality \({{\bar {\tilde {\Delta }}}_{{b{\kern 1pt} '}}} > {{\bar {\tilde {\Delta }}}_{b}}\) follows from the construction in accordance with the assertion algorithm:
Multiplying both sides of the inequality by \(i(i + ({{n}_{b}} - i)\), we get
By adding to both parts of the last inequality the quantity
we find
It follows that the splitting of any group formed by the statement algorithm into two subgroups leads to the fact that the resulting subgroups do not satisfy the minimum order relation \(\bar {\tilde {\Delta }}\), but they cannot be swapped because of the relation of precedence in the group.
Let us now show that the displacement \(b{\kern 1pt} '\) forward or \(b{\kern 1pt} ''\) back is impractical. Let in the original description a and c be subgroups, the first of which precedes b, and the second one follows b, i.e.
Subgroup \(b{\kern 1pt} '\) cannot be placed before a because
It cannot be carried further forward because for any subgroup preceding a the value \(\bar {\tilde {\Delta }}\) does not exceed \({{\bar {\tilde {\Delta }}}_{a}}\). Subgroup \(b{\kern 1pt} '\) cannot be placed inside a, dividing a into two parts \(a{\kern 1pt} '\) and \(a{\kern 1pt} ''\) because
and \(b{\kern 1pt} '\) cannot be placed before \(a{\kern 1pt} ''\). Similarly, it is proved that \(b{\kern 1pt} ''\) cannot be placed inside or after c.
Rights and permissions
About this article
Cite this article
Gruzlikov, A.M., Kolesov, N.V., Litunenko, E.G. et al. Optimization of Information Exchange in a Network of Autonomous Participants. J. Comput. Syst. Sci. Int. 61, 935–943 (2022). https://doi.org/10.1134/S1064230722060107
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S1064230722060107